Top 5 recent research courses on machine learning- simpliv
If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.
https://www.simpliv.com/search/sub-category/machinelearning
IRJET- Voice to Code Editor using Speech RecognitionIRJET Journal
This document presents a summary of a research paper on developing a voice-controlled code editor using speech recognition. A team of students and a professor from S.B Jain Institute of Technology, Management and Research created a Java program editor that allows users to write code using voice commands. The editor takes advantage of the natural human ability to speak language and allows coding more accurately and intuitively compared to manual typing. It analyzes the user's speech using acoustic and language modeling with Hidden Markov Models to accurately recognize commands. The proposed voice-controlled code editor is designed to reduce typing errors, improve coding speed, and enable people with disabilities to operate a computer. It will support basic editing tasks and allow switching between voice and manual input.
This document discusses coding, artificial intelligence (AI), and their importance for children's education. It notes that coding is the process of communicating with computers and is the basis of digital technologies. AI involves computers performing tasks that usually require human intelligence. The document recommends that children learn AI and coding from a young age, as these skills will be important for future careers and daily life. It provides examples of coding languages like Python and AI technologies. It also references the New Education Policy 2020 which recommends introducing subjects like AI and coding in schools.
Sushil Kumar Soni is seeking a challenging career that allows him to enhance his technical skills. He has a B.Tech in electronics and communications engineering from Mewar University with a score of 67.8% and a postgraduate diploma in DESD from C-DAC Noida with 66%. His skills include programming in C and Linux, working with AVR microcontrollers and PLC/SCADA systems. He has completed projects on automatic security systems and water level indicators.
IRJET- Online Programming Assessment and Evaluation Platform in Education SystemIRJET Journal
The document describes an online programming assessment and evaluation platform for educational institutions. It proposes developing a system that allows HODs to assign batches to faculty, who can then create programming assignments and assessments with test cases. Students would access the system to complete assignments, which would be automatically compiled and evaluated. The system would provide performance feedback to students and reduce the effort of manual evaluation. It would be built with an Angular front-end and Spring Boot APIs backend, with compilation handled in the cloud. A chatbot is also proposed to help students with doubts. The system aims to make programming assessment more efficient and accessible while improving students' coding skills.
Sudarshan Singh Parmar is seeking a position that allows him to apply his technical skills and knowledge gained through his education and experience. He holds an M.Tech in Spatial Information Technology from Devi Ahilya University, Indore and a B.E. in Electronics and Communication Engineering from Rajiv Gandhi Technical University, Bhopal. His academic qualifications also include an S.S.C. in Science and an H.S.C. in all subjects. Parmar has one semester of teaching experience and one year of experience maintaining power line communication systems. His areas of interest include control systems, analog circuits, and remote sensing.
The document discusses "peacock terms" which Wikipedia defines as words that sound nice but don't provide useful information to help readers understand a topic. It provides examples of peacock terms related to Adobe Photoshop and FPT University and compares them to more informative alternatives. The document also includes brief biographical information about the author Hans Anderson and his background teaching at FPT University.
The document provides information about Nettech India's data science course. It discusses the high demand for data scientists and what data science entails, including organizing, packaging and delivering data. It also defines what a data scientist does. The course covers topics like natural language processing, OpenCV, deep learning, and Tableau. It provides overviews of each topic and what students will learn, such as applying deep learning models to tasks like machine translation and using OpenCV for image processing, recognition and detection.
IRJET- Voice to Code Editor using Speech RecognitionIRJET Journal
This document presents a summary of a research paper on developing a voice-controlled code editor using speech recognition. A team of students and a professor from S.B Jain Institute of Technology, Management and Research created a Java program editor that allows users to write code using voice commands. The editor takes advantage of the natural human ability to speak language and allows coding more accurately and intuitively compared to manual typing. It analyzes the user's speech using acoustic and language modeling with Hidden Markov Models to accurately recognize commands. The proposed voice-controlled code editor is designed to reduce typing errors, improve coding speed, and enable people with disabilities to operate a computer. It will support basic editing tasks and allow switching between voice and manual input.
This document discusses coding, artificial intelligence (AI), and their importance for children's education. It notes that coding is the process of communicating with computers and is the basis of digital technologies. AI involves computers performing tasks that usually require human intelligence. The document recommends that children learn AI and coding from a young age, as these skills will be important for future careers and daily life. It provides examples of coding languages like Python and AI technologies. It also references the New Education Policy 2020 which recommends introducing subjects like AI and coding in schools.
Sushil Kumar Soni is seeking a challenging career that allows him to enhance his technical skills. He has a B.Tech in electronics and communications engineering from Mewar University with a score of 67.8% and a postgraduate diploma in DESD from C-DAC Noida with 66%. His skills include programming in C and Linux, working with AVR microcontrollers and PLC/SCADA systems. He has completed projects on automatic security systems and water level indicators.
IRJET- Online Programming Assessment and Evaluation Platform in Education SystemIRJET Journal
The document describes an online programming assessment and evaluation platform for educational institutions. It proposes developing a system that allows HODs to assign batches to faculty, who can then create programming assignments and assessments with test cases. Students would access the system to complete assignments, which would be automatically compiled and evaluated. The system would provide performance feedback to students and reduce the effort of manual evaluation. It would be built with an Angular front-end and Spring Boot APIs backend, with compilation handled in the cloud. A chatbot is also proposed to help students with doubts. The system aims to make programming assessment more efficient and accessible while improving students' coding skills.
Sudarshan Singh Parmar is seeking a position that allows him to apply his technical skills and knowledge gained through his education and experience. He holds an M.Tech in Spatial Information Technology from Devi Ahilya University, Indore and a B.E. in Electronics and Communication Engineering from Rajiv Gandhi Technical University, Bhopal. His academic qualifications also include an S.S.C. in Science and an H.S.C. in all subjects. Parmar has one semester of teaching experience and one year of experience maintaining power line communication systems. His areas of interest include control systems, analog circuits, and remote sensing.
The document discusses "peacock terms" which Wikipedia defines as words that sound nice but don't provide useful information to help readers understand a topic. It provides examples of peacock terms related to Adobe Photoshop and FPT University and compares them to more informative alternatives. The document also includes brief biographical information about the author Hans Anderson and his background teaching at FPT University.
The document provides information about Nettech India's data science course. It discusses the high demand for data scientists and what data science entails, including organizing, packaging and delivering data. It also defines what a data scientist does. The course covers topics like natural language processing, OpenCV, deep learning, and Tableau. It provides overviews of each topic and what students will learn, such as applying deep learning models to tasks like machine translation and using OpenCV for image processing, recognition and detection.
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach with online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach with online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach including online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
Learn How to Become an Expert in Artificial Intelligence With Our Roadmap
Imagine a machine arranging all your clothes as you like it or preparing customized food, considering each family member’s choice. Interesting, Isn’t it? This is what we call Artificial Intelligence.
Artificial Intelligence in today’s world is entering every domain in our daily lives, and we can undoubtedly conclude that the future of technology is here. From various voice assistants to chatbots, over all these years, Artificial Intelligence has proved that it indeed is here to stay. So why not seize the opportunity and build a career out of it?
In this article, we will share a concise introduction to artificial intelligence and which skills can assist you in creating a vocation in this field. This is just a microscopic viewpoint of the explicit learn path, link of which is mentioned at the end of the article.
What is Artificial Intelligence?
Emerging technologies like Artificial Intelligence and Data Science have made our life easier. Artificial intelligence, or AI as it’s more commonly called, alludes to the reenactment of human insight in machines that are modified to think like and copy humans.
It is the development of computer systems that can perform tasks that predominantly require human intelligence. These include visual perception, decision-making, speech recognition, and language translation.
Educational Requirements
Artificial Intelligence is a highly demanding and skill-intensive field. Since it is related to computer science, it needs a certain level of technical expertise and technological know-how. Hence, before even starting with the learning process, the primary prerequisite you must meet is a Bachelor’s degree in fields relevant to Artificial Intelligence such as Computer Science, Engineering, Mathematics, Statistics, and Information Technology.
If you have a Bachelor’s degree in math-intensive fields such as Economics and Finance, that can help you kickstart your journey in Artificial Intelligence as well.
Board Infinity Data Science Brochure - data science learning pathBoard Infinity
Join our Data Science Course to become a Certified Data Scientist! Master in the highly demanded technologies like SQL, Python alongside the concepts of Data Exploration, Regression Models, Hypothesis Testing. Get 1:1 personal coaching and mentoring straight from Top Data Science Coaches to be job-ready. This includes the complete data science syllabus, project, hackathons, and Data Science Certification.
Brochure data science learning path board-infinity (1)NirupamNishant2
Board Infinity is a best digital marketing and data science institute in mumbai, which is a full-stack career platform for students and jobseekers enabled by personalised learning paths,career coaches and access to various job oppurtunities. We provide online and offline training in Data Science, Digital Marketing, Full stack Web Development,Product management< machine learning and Atrificial Intelligence,Online career counselling and other career solutions
This document provides guidance on building a career in AI through three key steps: learning foundational skills, working on projects, and finding a job. It discusses each step in detail with chapters focused on learning technical skills, scoping AI projects, and using projects to complement career goals. The overall message is that an AI career requires lifelong learning, gaining experience through meaningful projects, and navigating an evolving job market. Building a supportive community is also important for support throughout the career journey.
*Uses of AI and data science can be found in almost any situation that produces data
* More uses for custom AI applications and data-derived
insights than for traditional software engineering
* Literacy in AI-oriented coding will be more valuable than traditional coding
A Comprehensive Learning Path to Become a Data Science 2021.pptxRajSingh512965
The 2021 data science learning path provides a comprehensive curriculum to become a data scientist. It includes extended skills in storytelling, model deployment, unsupervised learning, exercises, and projects. The path covers key skills and tools like Python, R, machine learning algorithms, deep learning, natural language processing, and model deployment. It consists of monthly modules that progress from the data science toolkit to advanced topics, with hands-on training and real-world projects.
This document provides information about a Data Scientist Master's Program offered in collaboration between Simplilearn and IBM. The program aims to accelerate careers in data science through world-class training on in-demand data science and machine learning skills like Python, R, Tableau, and machine learning concepts. It consists of 5 core courses covering topics like Python, data science with Python, machine learning, Tableau, and a capstone project. It also offers electives and provides certificates, projects, mentorship, and other resources to help students learn. The program is suitable for professionals of all backgrounds looking to enter or advance in a data science career.
This document provides information about a Data Scientist Master's Program offered in collaboration between Simplilearn and IBM. The program aims to accelerate careers in data science through world-class training on in-demand data science and machine learning skills. It offers extensive training on Python, R, Tableau, machine learning concepts and hands-on experience with tools and technologies. The program includes courses, electives, projects, certificates and support from IBM experts to help students gain expertise in data science.
This document summarizes a MOOC course on Python taken through the Udemy platform. The 35.5 hour course was created by Jose Salvatierra and teaches Python programming fundamentals through video lectures, presentations, quizzes and coding exercises over 4 weeks. Key topics covered include Python syntax, object oriented programming, graphical user interfaces, databases, and how Python can be applied to build complex AI products and address issues like bias, attacks, and ethics. Upon completion, students will have skills in core Python programming, OOP, GUI development, and database applications.
Computer Courses in Delhi.: Learners must be careful while selecting a career. With limited career possibilities, unemployment and contest among young individuals have grown.
Information Technology (IT) is a tremendously increasing sector that has achieved momentum over the previous few years. In today’s time planet, it is a must to have some understanding of computer-related information.
Understanding GenAI/LLM and What is Google Offering - Felix GohNUS-ISS
With the recent buzz on Generative AI & Large Language Models, the question is to what extent can these technologies be applied at work or when you're studying and how easy is it to manage/develop your own models? Hear from our guest speaker from Google as he shares some insights into how industries are evolving with these trends and what are some of Google's offerings from Duet AI in Google Workspace to the GenAI App Builder on Google Cloud.
Learnbay is the best data science trainer among other institutes in Bangalore. The data science course in Bangalore provides you with multiple IBM certifications and 16+ live projects, plus dedicated job placement.
Visit: https://www.learnbay.co/data-science-certification-courses
The document provides information about an online M.Tech degree program in Artificial Intelligence and Machine Learning offered by Intellipaat in collaboration with IIT Jammu. The 2-year program aims to provide in-depth knowledge of core AI and ML skills like Python, SQL, Apache Spark, neural networks etc. It focuses on building a strong profile for professionals and aspirants in the fast growing domain of AI and ML. The program curriculum includes courses across 4 semesters covering topics like machine learning, deep learning, image processing etc.
Best Artificial Intelligence Course | Online program | certification course Learn and Build
Learn Understand and solve complex machine learning problems with programming language skills and become AI experts, explore opportunities for data engineering, AI engineering, Software engineering and a lot more. Get enrolled now, learn anywhere and get an online certification Artificial Intelligence course.
Artificial intelligence in android developmentanikeshkumar11
Artificial intelligence is making machines capable of learning and interacting like humans to assist with tasks. AI applications that can be integrated into Android apps include automated reasoning, image labeling, face detection, text recognition, and curating personalized content. Google has shifted priorities to "AI First" and released new toolkits to promote AI development on Android. Key frameworks for deploying AI and machine learning in Android include TensorFlow, PyTorch, Google Cloud ML, Firebase ML Kit, and OpenCV. A TensorFlow model can be trained on Android by collecting and preprocessing data, creating labeled image folders, retraining the model, optimizing for devices, and embedding the .tflite file.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
More Related Content
Similar to Top 5 recent research courses on machine learning- simpliv
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach with online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach with online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
This document provides an overview of an AI and Applications bootcamp program. The program includes a variety of courses that provide both theoretical foundations and practical skills in AI, machine learning, and related topics. It utilizes a blended learning approach including online videos, live virtual classes, projects, and masterclasses. The program aims to help professionals gain expertise in in-demand AI skills and advance their careers. It covers topics such as deep learning, computer vision, natural language processing, and more.
Learn How to Become an Expert in Artificial Intelligence With Our Roadmap
Imagine a machine arranging all your clothes as you like it or preparing customized food, considering each family member’s choice. Interesting, Isn’t it? This is what we call Artificial Intelligence.
Artificial Intelligence in today’s world is entering every domain in our daily lives, and we can undoubtedly conclude that the future of technology is here. From various voice assistants to chatbots, over all these years, Artificial Intelligence has proved that it indeed is here to stay. So why not seize the opportunity and build a career out of it?
In this article, we will share a concise introduction to artificial intelligence and which skills can assist you in creating a vocation in this field. This is just a microscopic viewpoint of the explicit learn path, link of which is mentioned at the end of the article.
What is Artificial Intelligence?
Emerging technologies like Artificial Intelligence and Data Science have made our life easier. Artificial intelligence, or AI as it’s more commonly called, alludes to the reenactment of human insight in machines that are modified to think like and copy humans.
It is the development of computer systems that can perform tasks that predominantly require human intelligence. These include visual perception, decision-making, speech recognition, and language translation.
Educational Requirements
Artificial Intelligence is a highly demanding and skill-intensive field. Since it is related to computer science, it needs a certain level of technical expertise and technological know-how. Hence, before even starting with the learning process, the primary prerequisite you must meet is a Bachelor’s degree in fields relevant to Artificial Intelligence such as Computer Science, Engineering, Mathematics, Statistics, and Information Technology.
If you have a Bachelor’s degree in math-intensive fields such as Economics and Finance, that can help you kickstart your journey in Artificial Intelligence as well.
Board Infinity Data Science Brochure - data science learning pathBoard Infinity
Join our Data Science Course to become a Certified Data Scientist! Master in the highly demanded technologies like SQL, Python alongside the concepts of Data Exploration, Regression Models, Hypothesis Testing. Get 1:1 personal coaching and mentoring straight from Top Data Science Coaches to be job-ready. This includes the complete data science syllabus, project, hackathons, and Data Science Certification.
Brochure data science learning path board-infinity (1)NirupamNishant2
Board Infinity is a best digital marketing and data science institute in mumbai, which is a full-stack career platform for students and jobseekers enabled by personalised learning paths,career coaches and access to various job oppurtunities. We provide online and offline training in Data Science, Digital Marketing, Full stack Web Development,Product management< machine learning and Atrificial Intelligence,Online career counselling and other career solutions
This document provides guidance on building a career in AI through three key steps: learning foundational skills, working on projects, and finding a job. It discusses each step in detail with chapters focused on learning technical skills, scoping AI projects, and using projects to complement career goals. The overall message is that an AI career requires lifelong learning, gaining experience through meaningful projects, and navigating an evolving job market. Building a supportive community is also important for support throughout the career journey.
*Uses of AI and data science can be found in almost any situation that produces data
* More uses for custom AI applications and data-derived
insights than for traditional software engineering
* Literacy in AI-oriented coding will be more valuable than traditional coding
A Comprehensive Learning Path to Become a Data Science 2021.pptxRajSingh512965
The 2021 data science learning path provides a comprehensive curriculum to become a data scientist. It includes extended skills in storytelling, model deployment, unsupervised learning, exercises, and projects. The path covers key skills and tools like Python, R, machine learning algorithms, deep learning, natural language processing, and model deployment. It consists of monthly modules that progress from the data science toolkit to advanced topics, with hands-on training and real-world projects.
This document provides information about a Data Scientist Master's Program offered in collaboration between Simplilearn and IBM. The program aims to accelerate careers in data science through world-class training on in-demand data science and machine learning skills like Python, R, Tableau, and machine learning concepts. It consists of 5 core courses covering topics like Python, data science with Python, machine learning, Tableau, and a capstone project. It also offers electives and provides certificates, projects, mentorship, and other resources to help students learn. The program is suitable for professionals of all backgrounds looking to enter or advance in a data science career.
This document provides information about a Data Scientist Master's Program offered in collaboration between Simplilearn and IBM. The program aims to accelerate careers in data science through world-class training on in-demand data science and machine learning skills. It offers extensive training on Python, R, Tableau, machine learning concepts and hands-on experience with tools and technologies. The program includes courses, electives, projects, certificates and support from IBM experts to help students gain expertise in data science.
This document summarizes a MOOC course on Python taken through the Udemy platform. The 35.5 hour course was created by Jose Salvatierra and teaches Python programming fundamentals through video lectures, presentations, quizzes and coding exercises over 4 weeks. Key topics covered include Python syntax, object oriented programming, graphical user interfaces, databases, and how Python can be applied to build complex AI products and address issues like bias, attacks, and ethics. Upon completion, students will have skills in core Python programming, OOP, GUI development, and database applications.
Computer Courses in Delhi.: Learners must be careful while selecting a career. With limited career possibilities, unemployment and contest among young individuals have grown.
Information Technology (IT) is a tremendously increasing sector that has achieved momentum over the previous few years. In today’s time planet, it is a must to have some understanding of computer-related information.
Understanding GenAI/LLM and What is Google Offering - Felix GohNUS-ISS
With the recent buzz on Generative AI & Large Language Models, the question is to what extent can these technologies be applied at work or when you're studying and how easy is it to manage/develop your own models? Hear from our guest speaker from Google as he shares some insights into how industries are evolving with these trends and what are some of Google's offerings from Duet AI in Google Workspace to the GenAI App Builder on Google Cloud.
Learnbay is the best data science trainer among other institutes in Bangalore. The data science course in Bangalore provides you with multiple IBM certifications and 16+ live projects, plus dedicated job placement.
Visit: https://www.learnbay.co/data-science-certification-courses
The document provides information about an online M.Tech degree program in Artificial Intelligence and Machine Learning offered by Intellipaat in collaboration with IIT Jammu. The 2-year program aims to provide in-depth knowledge of core AI and ML skills like Python, SQL, Apache Spark, neural networks etc. It focuses on building a strong profile for professionals and aspirants in the fast growing domain of AI and ML. The program curriculum includes courses across 4 semesters covering topics like machine learning, deep learning, image processing etc.
Best Artificial Intelligence Course | Online program | certification course Learn and Build
Learn Understand and solve complex machine learning problems with programming language skills and become AI experts, explore opportunities for data engineering, AI engineering, Software engineering and a lot more. Get enrolled now, learn anywhere and get an online certification Artificial Intelligence course.
Artificial intelligence in android developmentanikeshkumar11
Artificial intelligence is making machines capable of learning and interacting like humans to assist with tasks. AI applications that can be integrated into Android apps include automated reasoning, image labeling, face detection, text recognition, and curating personalized content. Google has shifted priorities to "AI First" and released new toolkits to promote AI development on Android. Key frameworks for deploying AI and machine learning in Android include TensorFlow, PyTorch, Google Cloud ML, Firebase ML Kit, and OpenCV. A TensorFlow model can be trained on Android by collecting and preprocessing data, creating labeled image folders, retraining the model, optimizing for devices, and embedding the .tflite file.
Similar to Top 5 recent research courses on machine learning- simpliv (20)
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Top 5 recent research courses on machine learning- simpliv
1. 1. Statistics and Data Science in R
Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst.
This team has decades of practical experience in quant trading, analytics and e-commerce.
This course is a gentle yet thorough introduction to Data Science, Statistics and R using real life
examples.
Let’s parse that.
Gentle, yet thorough: This course does not require a prior quantitative or mathematics
background. It starts by introducing basic concepts such as the mean, median etc and
eventually covers all aspects of an analytics (or) data science career from analysing and
preparing raw data to visualising your findings.
2. Data Science, Statistics and R: This course is an introduction to Data Science and
Statistics using the R programming language. It covers both the theoretical aspects of
Statistical concepts and the practical implementation using R.
Real life examples: Every concept is explained with the help of examples, case studies
and source code in R wherever necessary. The examples cover a wide array of topics and
range from A/B testing in an Internet company context to the Capital Asset Pricing
Model in a quant finance context.
What's Covered:
Data Analysis with R: Datatypes and Data structures in R, Vectors, Arrays, Matrices,
Lists, Data Frames, Reading data from files, Aggregating, Sorting & Merging Data
Frames
Linear Regression: Regression, Simple Linear Regression in Excel, Simple Linear
Regression in R, Multiple Linear Regression in R, Categorical variables in regression,
Robust regression, Parsing regression diagnostic plots
Data Visualization in R: Line plot, Scatter plot, Bar plot, Histogram, Scatterplot matrix,
Heat map, Packages for Data Visualisation : Rcolorbrewer, ggplot2
Descriptive Statistics: Mean, Median, Mode, IQR, Standard Deviation, Frequency
Distributions, Histograms, Boxplots
Inferential Statistics: Random Variables, Probability Distributions, Uniform Distribution,
Normal Distribution, Sampling, Sampling Distribution, Hypothesis testing, Test statistic,
Test of significance
3. Using discussion forums
Please use the discussion forums on this course to engage with other students and to help each
other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to
respond to individual questions from students:-(
We're super small and self-funded with only 2 people developing technical video content. Our
mission is to make high-quality courses available at super low prices.
The only way to keep our prices this low is to *NOToffer additional technical support over
email or in-person*. The truth is, direct support is hugely expensive and just does not scale.
We understand that this is not ideal and that a lot of students might benefit from this additional
support. Hiring resources for additional support would make our offering much more expensive,
thus defeating our original purpose.
It is a hard trade-off.
Thank you for your patience and understanding!
Who is the target audience?
Yep! MBA graduates or business professionals who are looking to move to a heavily
quantitative role
Yep! Engineers who want to understand basic statistics and lay a foundation for a career
in Data Science
Yep! Analytics professionals who have mostly worked in Descriptive analytics and want
to make the shift to being modelers or data scientists
Yep! Folks who've worked mostly with tools like Excel and want to learn how to use R
for statistical analysis
Basic knowledge
No prerequisites : We start from basics and cover everything you need to know. We will
be installing R and RStudio as part of the course and using it for most of the examples.
Excel is used for one of the examples and basic knowledge of excel is assumed.
What you will learn
Harness R and R packages to read, process and visualize data
Understand linear regression and use it confidently to build models
Understand the intricacies of all the different data structures in R
Use Linear regression in R to overcome the difficulties of LINEST() in Excel
Draw inferences from data and support them using tests of significance
Use descriptive statistics to perform a quick study of some data and present results
4. Are you ready to join us to Keep Growing Up
2. Complete iOS 11 Machine Learning Masterclass
If you want to learn how to start building professional, career-boosting mobile apps and use
Machine Learning to take things to the next level, then this course is for you. The Complete iOS
Machine Learning Masterclass™ is the only course that you need for machine learning on iOS.
Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants
like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS
Machine Learning technology stacks to add a layer of intelligence and polish to your mobile
apps. We’re approaching a new era where only apps and games that are considered “smart” will
survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the
curve and adopt this innovative approach; the Complete iOS Machine Learning
Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.
In this course, you will:
Master the 3 fundamental branches of applied Machine Learning: Image & Video
Processing, Text Analysis, and Speech & Language Recognition
Develop an intuitive sense for using Machine Learning in your iOS apps
Create 7 projects from scratch in practical code-along tutorials
Find pre-trained ML models and make them ready to use in your iOS apps
Create your own custom models
Add Image Recognition capability to your apps
5. Integrate Live Video Camera Stream Object Recognition to your apps
Add Siri Voice speaking feature to your apps
Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and
GamePlayKit.
Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–
even if you have zero experience
Get FREE unlimited hosting for one year
And more!
This course is also full of practical use cases and real-world challenges that allow you to practice
what you’re learning. Are you tired of courses based on boring, over-used examples? Yes? Well
then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics
such as image recognition, object recognition, and modifying existing trained ML models. You’ll
also create an app that classifies flowers and another fun project inspired by Silicon
Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app!
Why Machine Learning on iOS
One of the hottest growing fields in technology today, Machine Learning is an excellent skill to
boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s
hottest companies are working to make Machine Learning an essential part of our daily lives.
Self-driving cars are just around the corner with millions of miles of successful training. IBM’s
Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google
DeepMind’s computer, can beat the world master of the game Go, a game where it was thought
only human intuition could excel.
In 2017, Apple has made Machine Learning available in iOS 11 so that anyone can build smart
apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games
that do not have an ML layer will not be appealing to users. Whether you wish to change careers
or create a second stream of income, Machine Learning is a highly lucrative skill that can give
you an amazing sense of gratification when you can apply it to your mobile apps and games.
6. Why This Course Is Different
Machine Learning is very broad and complex; to navigate this maze, you need a clear and global
vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In
this course, each section focuses on distinct use cases and real projects so that your learning
experience is best structured for mastery.
This course brings my teaching experience and technical know-how to you. I’ve taught
programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience
making top-ranked apps. For each project, we will write up the code line by line to create it from
scratch. This way you can follow along and understand exactly what each line means and how to
code comes together. Once you go through the hands-on coding exercises, you will see for
yourself how much of a game-changing experience this course is.
As an educator, I also want you to succeed. I’ve put together a team of professionals to help you
master the material. Whenever you ask a question, you will get a response from my team within
48 hours. No matter how complex your question, we will be there–because we feel a personal
responsibility in being fully committed to our students.
By the end of the course, you will confidently understand the tools and techniques of Machine
Learning for iOS on an instinctive level.
Don’t be the one to get left behind. Get started today and join millions of people taking part in
the Machine Learning revolution.
topics: ios 11 swift 4 coreml vision deep learning machine learning neural networks python
anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial
neural network ANN recurrent neural network RNN convolutional neural network CNN ocr
character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning
neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11
Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional
neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep
learning machine learning neural networks python anaconda trained models keras tensorflow
scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural
network RNN convolutional neural network CNN ocr character recognition face detection ios 11
swift 4 coreml vision deep learning machine learning neural networks python anaconda trained
models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network
ANN recurrent neural network RNN convolutional neural network CNN ocr character
recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural
networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4
scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural
network CNN ocr character recognition face detection
Who is the target audience?
7. People with a basic foundation in iOS programming who would like to discover Machine
Learning, a branch of Artificial Intelligence
People who want to pursue a career combining app development and Machine Learning
to become a hybrid iOS developer and ML expert
Developers who would like to apply their Machine Learning skills by creating practical
mobile apps
Entrepreneurs who want to leverage the exponential technology of Machine Learning to
create added value to their business could also take this course. However, this course
does assume that you are familiar with basic programming concepts such as object
oriented programming, variables, methods, classes, and conditional statements
Basic knowledge
Basic understanding of programming
Have access to a MAC computer or MACinCloud website
What you will learn
Build smart iOS 11 & Swift 4 apps using Machine Learning
Use trained ML models in your apps
Convert ML models to iOS ready models
Create your own ML models
Apply Object Prediction on pictures, videos, speech and text
Discover when and how to apply a smart sense to your apps
Are you ready to join us to Keep Growing Up
3. Introduction to Data Science with Python
8.
9. This course introduces Python programming as a way to have hands-on experience with Data
Science. It starts with a few basic examples in Python before moving onto doing statistical
processing. The course then introduces Machine Learning with techniques such as regression,
classification, clustering, and density estimation, in order to solve various data problems.
Basic knowledge
This course is for beginners, but it helps to have some basic understanding of statistics
(mean, median, scatter plot) and preliminary knowledge of any programming. The course
also assumes that you know how to download and install various programs/apps, and you
are able to edit and debug simple programs
What you will learn
Writing simple Python scripts to do basic mathematical and logical operations
Loading structured data in a Python environment for processing
Creating descriptive statistics and visualizations
Finding correlations among numerical variables
Using regression analysis to predict the value of a continuous variable
Building classification models to organize data into pre-determined classes
Organizing given data into meaningful clusters
Applying basic machine learning techniques for solving various data problems
Are you ready to join us to Keep Growing Up
4. Introduction to Data Science with R
10. This course introduces R programming environment as a way to have hands-on experience with
Data Science. It starts with a few basic examples in R before moving onto doing statistical
processing. The course then introduces Machine Learning with techniques such as regression,
classification, clustering, and density estimation, in order to solve various data problems.
Basic knowledge
This course is for beginners, but it helps to have some basic understanding of statistics
(mean, median, scatter plot) and preliminary knowledge of any programming. The course
also assumes that you know how to download and install various programs/apps, and you
are able to edit and debug simple programs
What you will learn
Writing simple R programs to do basic mathematical and logical operations
Loading structured data in a R environment for processing
Creating descriptive statistics and visualizations
Finding correlations among numerical variables
Using regression analysis to predict the value of a continuous variable
Building classification models to organize data into pre-determined classes
Organizing given data into meaningful clusters
Applying basic machine learning techniques for solving various data problems
Are you ready to join us to Keep Growing Up
5. Machine Learning In The Cloud With Azure Machine
Learning
11. The history of data science, machine learning, and artificial Intelligence is long, but it’s only
recently that technology companies - both start-ups and tech giants across the globe have begun
to get excited about it… Why? Because now it works. With the arrival of cloud computing and
multi-core machines - we have enough compute capacity at our disposal to churn large volumes
of data and dig out the hidden patterns contained in these mountains of data.
This technology comes in handy, especially when handling Big Data. Today, companies collect
and accumulate data at massive, unmanageable rates for website clicks, credit card transactions,
GPS trails, social media interactions, and so on. And it is becoming a challenge to process all the
valuable information and use it in a meaningful way. This is where machine learning algorithms
come into the picture. These algorithms use all the collected “past” data to learn patterns and
predict results or insights that help us make better decisions backed by actual analysis.
You may have experienced various examples of Machine Learning in your daily life (in some
cases without even realizing it). Take for example
Credit scoring, which helps the banks to decide whether to grant the loans to a particular
customer or not - based on their credit history, historical loan applications, customers’ data and
so on
Or the latest technological revolution from right from science fiction movies – the self-driving
cars, which use Computer vision, image processing, and machine learning algorithms to learn
from actual drivers’ behavior.
Or Amazon's recommendation engine which recommends products based on buying patterns of
millions of consumers.
In all these examples, machine learning is used to build models from historical data, to forecast
the future events with an acceptable level of reliability. This concept is known as Predictive
12. analytics. To get more accuracy in the analysis, we can also combine machine learning with
other techniques such as data mining or statistical modeling.
This progress in the field of machine learning is great news for the tech industry and humanity in
general.
But the downside is that there aren’t enough data scientists or machine learning engineers who
understand these complex topics.
Well, what if there was an easy to use a web service in the cloud - which could do most of the
heavy lifting for us? What if scaled dynamically based on our data volume and velocity?
The answer - is new cloud service from Microsoft called Azure Machine Learning. Azure
Machine Learning is a cloud-based data science and machine learning service which is easy to
use and is robust and scalable like other Azure cloud services. It provides visual and
collaborative tools to create a predictive model which will be ready-to-consume on web services
without worrying about the hardware or the VMs which perform the calculations.
The advantage of Azure ML is that it provides a UI-based interface and pre-defined algorithms
that can be used to create a training model. And it also supports various programming and
scripting languages like R and Python.
In this course, we will discuss Azure Machine Learning in detail. You will learn what features it
provides and how it is used. We will explore how to process some real-world datasets and find
some patterns in that dataset.
Do you know what it takes to build sophisticated machine learning models in the cloud?
How to expose these models in the form of web services?
13. Do you know how you can share your machine learning models with non-technical knowledge
workers and hand them the power of data analysis?
These are some of the fundamental problems data scientists and engineers struggle with on a
daily basis.
This course teaches you how to design, deploy, configure and manage your machine learning
models with Azure Machine Learning. The course will start with an introduction to the Azure
ML toolset and features provided by it and then dive deeper into building some machine learning
models based on some real-world problems.
If you’re serious about building scalable, flexible and powerful machine learning models in the
cloud, then this course is for you.
These data science skills are in great demand, but there’s no easy way to acquire this knowledge.
Rather than rely on hit and trial method, this course will provide you with all the information you
need to get started with your machine learning projects.
Startups and technology companies pay big bucks for experience and skills in these technologies
They demand data science and cloud engineers make sense of their dormant data collected on
their servers - and in turn, you can demand top dollar for your abilities.
You may be a data science veteran or an enthusiast - if you invest your time and bring an
eagerness to learn, we guarantee you real, actionable education at a fraction of the cost you can
demand as a data science engineer or a consultant. We are confident your investment will come
back to you many-fold in no time.
14. So, if you're ready to make a change and learn how to build some cool machine learning models
in the cloud, click the "Add to Cart" button below.
Look, if you're serious about becoming an expert data engineer and generating a greater income
for you and your family, it’s time to take action.
Imagine getting that promotion which you’ve been promised for the last two presidential terms.
Imagine getting chased by recruiters looking for skilled and experienced engineers by companies
that are desperately seeking help. We call those good problems to have.
Imagine getting a massive bump in your income because of your newly-acquired, in-demand
skills.
That’s what we want for you. If that’s what you want for yourself, click the “Add to Cart” button
below and get started today with our “Machine Learning In The Cloud With Azure Machine
Learning”.
Let’s do this together!
Who is the target audience?
Data science enthusiasts
Software and IT engineers
Statisticians
Cloud engineers
Software architects
Technical and non-technical tech founders
Basic knowledge
Access to a free or paid account for Azure
Basic knowledge about cloud computing and data science
Basic knowledge about IT infrastructure setup
Desire to learn something new and continuous improvement
What you will learn
Learn about Azure Machine Learning
Learn about various machine learning algorithms supported by Azure Machine Learning
Learn how to build and run a machine learning experiment with real world datasets
Learn how to use classification machine learning algorithms
Learn how to use regression machine learning algorithms
Learn how to expose the Azure ML machine learning experiment as a web service or API
Learn how to integrate the Azure ML machine learning experiment API with a web
application
15. Are you ready to join us to Keep Growing Up
Click to Continue Reading:
Simpliv Youtube Course & Tutorial :