Machine learning_snap#3
•Download as PPTX, PDF•
1 like•81 views
This document provides an overview of machine learning. It discusses how machine learning finds patterns in data and is used to predict the future based on past data. It also contrasts machine learning with traditional programming by noting that machine learning uses example data to generate an output rather than being explicitly programmed. The document lists reasons for using machine learning like no human experts being available or rapidly changing phenomena. It provides resources for machine learning including technical papers, journals, conferences and datasets. It concludes by listing several references on machine learning.
Report
Share
Report
Share
Recommended
GTU GeekDay 2019 Limitations of Artificial Intelligence
Artificial intelligence has limitations related to its technical abilities, practical implementation, and applications. Technically, AI models lack interpretability and explainability, meaning they cannot clearly explain their decisions. Practically, AI is limited by data biases from human and technical factors as well as by lack of data. In applications, AI cannot match all human abilities and raises concerns about job loss, ethics, and uncontrolled advancement. Overall, while AI has advantages like accuracy and endurance, its limitations must be addressed through techniques such as explainable AI, data augmentation, and reinforcement learning.
Machine Learning for Data Extraction
Presented at OECD Workshop on Systematic Reviews in the Scope of the Endocrine Disrupter Testing and Assessment (EDTA) Conceptual Framework Level 1 in Paris, France
intro to ML by the way m toh phasee movie Punjabi
This document provides an overview of machine learning including:
- Defining machine learning as automating automation by getting computers to program themselves using data instead of hand-written programs.
- Describing supervised, unsupervised, semi-supervised, and reinforcement learning.
- Providing examples of machine learning applications like web search, computational biology, finance, robotics, and social networks.
- Explaining core machine learning concepts like representation, evaluation, and optimization as well as inductive learning from examples.
Role of IT in Research: How to improve productivity of Research Process
Research is nothing but satisfying the quest. While pursuing a typical research process, lot of time is spent on non value adding activities and this study guides you on how IT can simplify and expedite the research.
influence of AI in IS
Artificial intelligence and machine learning are increasingly being adopted across industries. AI comes in various forms like narrow AI, general AI, and deep learning. Machine learning algorithms like supervised learning, unsupervised learning and reinforcement learning are used to build AI systems. The document discusses how AI is being used in security applications like malware detection. It also covers emerging technologies like the Internet of Things and associated security issues due to lack of encryption and authentication in many IoT devices.
lec01.ppt
1. The document introduces databases and their history, from early data storage and retrieval to modern database management systems.
2. It discusses Edgar Codd's invention of the relational database model in 1970 which changed the field by separating data from application code for easier modification and generalization.
3. The document outlines what a database management system does, including managing large amounts of data, supporting efficient and concurrent access, and providing security.
Die Bedeutung von Machine Learning für den e-Commerce am Beispiel von Amazon
Ralf Herbrich gave a presentation on machine learning at Amazon. Some key points included:
- He discussed his background and experience in machine learning from 1992 to the present.
- The presentation provided an overview of machine learning including definitions from computer science and statistics perspectives, the history of machine learning, and examples of machine learning applications at Amazon like forecasting, machine translation, and visual systems.
Teaching Machine Learning with Physical Computing - July 2023
This document provides an overview of resources for teaching machine learning and artificial intelligence concepts to K-12 students. It discusses machine learning concepts and workflows. It then lists and briefly describes various hardware platforms, software tools, curricula, and online resources that can be used to teach machine learning, including platforms for visual programming languages like Scratch and Blockly.
Recommended
GTU GeekDay 2019 Limitations of Artificial Intelligence
Artificial intelligence has limitations related to its technical abilities, practical implementation, and applications. Technically, AI models lack interpretability and explainability, meaning they cannot clearly explain their decisions. Practically, AI is limited by data biases from human and technical factors as well as by lack of data. In applications, AI cannot match all human abilities and raises concerns about job loss, ethics, and uncontrolled advancement. Overall, while AI has advantages like accuracy and endurance, its limitations must be addressed through techniques such as explainable AI, data augmentation, and reinforcement learning.
Machine Learning for Data Extraction
Presented at OECD Workshop on Systematic Reviews in the Scope of the Endocrine Disrupter Testing and Assessment (EDTA) Conceptual Framework Level 1 in Paris, France
intro to ML by the way m toh phasee movie Punjabi
This document provides an overview of machine learning including:
- Defining machine learning as automating automation by getting computers to program themselves using data instead of hand-written programs.
- Describing supervised, unsupervised, semi-supervised, and reinforcement learning.
- Providing examples of machine learning applications like web search, computational biology, finance, robotics, and social networks.
- Explaining core machine learning concepts like representation, evaluation, and optimization as well as inductive learning from examples.
Role of IT in Research: How to improve productivity of Research Process
Research is nothing but satisfying the quest. While pursuing a typical research process, lot of time is spent on non value adding activities and this study guides you on how IT can simplify and expedite the research.
influence of AI in IS
Artificial intelligence and machine learning are increasingly being adopted across industries. AI comes in various forms like narrow AI, general AI, and deep learning. Machine learning algorithms like supervised learning, unsupervised learning and reinforcement learning are used to build AI systems. The document discusses how AI is being used in security applications like malware detection. It also covers emerging technologies like the Internet of Things and associated security issues due to lack of encryption and authentication in many IoT devices.
lec01.ppt
1. The document introduces databases and their history, from early data storage and retrieval to modern database management systems.
2. It discusses Edgar Codd's invention of the relational database model in 1970 which changed the field by separating data from application code for easier modification and generalization.
3. The document outlines what a database management system does, including managing large amounts of data, supporting efficient and concurrent access, and providing security.
Die Bedeutung von Machine Learning für den e-Commerce am Beispiel von Amazon
Ralf Herbrich gave a presentation on machine learning at Amazon. Some key points included:
- He discussed his background and experience in machine learning from 1992 to the present.
- The presentation provided an overview of machine learning including definitions from computer science and statistics perspectives, the history of machine learning, and examples of machine learning applications at Amazon like forecasting, machine translation, and visual systems.
Teaching Machine Learning with Physical Computing - July 2023
This document provides an overview of resources for teaching machine learning and artificial intelligence concepts to K-12 students. It discusses machine learning concepts and workflows. It then lists and briefly describes various hardware platforms, software tools, curricula, and online resources that can be used to teach machine learning, including platforms for visual programming languages like Scratch and Blockly.
antrikshindutrialmachinelearningPPT.pptx
This document provides an overview of machine learning and data science using Python. It introduces machine learning and data science, the Python programming language, popular integrated development environments for Python, and Google Colab. It also discusses types of machine learning algorithms, the machine learning process, important Python libraries, the data science life cycle, data visualization techniques, and the differences between machine learning and data science. The document outlines how to use Google Colab for machine learning and data science projects and provides information on the scope and applications of machine learning and data science.
Basics of Intelligent Computing.pdf
This document provides an overview of the IT201 Basics of Intelligent Computing course. It outlines the course outcomes, which include being able to distinguish AI branches, solve problems using techniques like fuzzy logic and genetic algorithms, design neural networks, and discuss cloud computing and IoT. It also describes the various modules that make up the course, including introductions to computing, intelligent computing, and artificial intelligence concepts. Specific techniques discussed for solving AI problems include search, use of knowledge, and abstraction. The document provides examples of different programming approaches for problems like tic-tac-toe and question answering.
Showcasing research data tools - Jisc Digifest 2016
The document summarizes several projects from Phase 3 of the Research Data Spring initiative. It describes DataVault, a platform for long-term archival of research data. It also discusses DMA Online, a dashboard that aggregates research data management information from multiple sources. Additionally, it outlines Clipper, a tool for creating and sharing clips from audiovisual materials. Finally, it presents a project that aims to incentivize data deposit by enabling researchers to publish "data papers" describing their datasets.
Showcasing research data tools
Demo at DigiFest 2016 on 4 of the research data spring funded projects that address research data management issues.
Software Mining and Software Datasets
This document discusses software mining and datasets. It begins by introducing Tao Xie and his research group at the University of Illinois which focuses on software analytics. It then discusses different types of software services and data, how data has become more pervasive, and challenges in making repositories more actionable. Key topics in software analytics research are discussed including the goal of enabling insights for practitioners. Examples of mined information from different repository types like source code, bug reports, and mailing lists are provided.
Data Science at Scale - The DevOps Approach
DevOps Practices for Data Scientists and Engineers
1 Data Science Landscape
2 Process and Flow
3 The Data
4 Data Science Toolkit
5 Cloud Computing Solutions
6 The rise of DevOps
7 Reusable Assets and Practices
8 Skills Development
Datat and donuts: how to write a data management plan
This document provides guidance on how to write a data management plan (DMP). It discusses what a DMP is, why researchers should care about data management, and where data management fits into the research cycle. It also covers the key components of a successful DMP, including a data inventory, a strategy for describing the data, a plan for long-term data preservation, and methods for making the data accessible. The document provides examples and exercises to help researchers develop the sections of a DMP for their own research projects.
Simbios - Open Science in Biocomputational Research
Presentation on the Simbios National Center for Biomedical Computing and our efforts to promote open source and open data within the biocomputational research community. Presented at the Stanford Open Source Lab (un)Conference, November 2008
The Ai & I at Work
The document provides a history of data science and artificial intelligence, discusses how the two fields intersect, and provides examples of practical coding techniques for data scientists using AI tools. It begins with a brief history of data science from the 1960s development of empirical data analysis to the modern role of data scientists. It then discusses the parallel history of AI from its origins in the 1950s to recent advances in deep learning. The document explains that data scientists today can focus on analysis or building machine learning models, and that Python is a common coding language in both fields. It offers Jupyter Notebooks, Google Collab, and Docker as tools and provides examples using sentiment analysis, Google AutoML, and AWS DeepLens.
AI and Healthcare: An Overview (January 2024)
Use this presentation to:
- learn about the historical roots of AI
- learn about major events in the AI timeline
- get an overview of some of the ways that AI is being used now in healthcare to facilitate provider-patient communication, mine medical records, assess patients, predict illness, suggest treatments, enable patient monitoring
This presentation is updated for early 2024 and addresses AI's use in the creation of dis/misinformation and deepfakes, as well as the bias inherent in AI, brought on by the data sets used to train it.
00-01 DSnDA.pdf
The document discusses the growth of data and the field of data science. It begins by noting the large amounts of data being generated daily by various sources like web/e-commerce transactions, social networks, and scientific projects. It then discusses some of the challenges of big data including volume, velocity, and variety. The document provides an overview of the multidisciplinary nature of data science and the skills required of data scientists. It also summarizes different approaches to and job roles in data science.
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
AI is the new ELECTRICITY - said Andrew Ng. There are two sides of the coin. There are a lot of nay-sayers for AI. At the end of the day, it will be Augmented Intelligence, Adaptive Intelligence, Automated Intelligence that will propel human intelligence forward - more than anything else. It will be a great time ahead. Whether it would be an "Eye(AI) Wash" as skeptics say or an "I wish" from them for starting late on the journey, only time will tell. It is a matter of when and how long, instead of an If. #ArtificialIntelligence #IntelligentTesting #QCoE #NextGenTesting #QualityFocusedDelivery #DigitalInnovation #ITIndustry #NewAgeIT #InnovativeTesting#AIFication #Automation #DigitalEconomy #Singularity #Transcendence #Futurism
Webinar: Machine Learning para Microcontroladores
Neste webinar, serão apresentados conceitos sobre inteligência artificial, assim como ferramentas disponíveis para o desenvolvimento integradas ao MPLAB X e ao Harmony 3 e demonstração de um sistema de detecção de anomalia utilizando um microcontrolador da família ATSAMD21 (ARM Cortex M0+).
Biostast
The document discusses the basics of computational biology and computer components. It defines computational biology as being hypothesis-driven and involving using mathematical modeling and simulation to study biological systems, giving modeling gene regulatory networks as an example. It also defines bioinformatics as being data-driven and involving using computational tools to analyze biological data, such as protein database searching. The document then provides basic information about computer components like memory types, CPU parts, and differences between primary and secondary memory.
Smarter Data for Smarter Libraries
This document discusses how libraries can leverage data from their collections to support new research and discovery. It outlines several initiatives that treat library collections as data, including the Library of Congress labs and a project exploring computationally-driven research. The document also discusses OCLC's work analyzing institutional repository data through its Repository Analytics and Metrics Portal (RAMP) and making data more interoperable through support of the IIIF standard for sharing images and metadata.
Intro to RDM
An introduction to Research Data Management and Data Sharing given via webinar for Diponegoro University, Indonesia
Elixir at de.nbi meeting
- Data transfer
- Compute access
- Training
Data Hub:
- Secure data sharing
- Data management
- Metadata catalogues
AAI:
- Single sign-on
- User attributes
- Group management
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
intelligentsystems-140424154432-phpapp01.pptx
This document provides an overview of intelligent systems (IS). It begins with defining three main categories of IS: industrial, household, and research. Several examples are given for each category, such as autonomous vehicles for industry, personal assistants like Siri for households, and nursing robots for research. The document then discusses major IS research centers around the world and some notable people and publications in the field of IS.
Introduction to Big Data and Data Science
The document provides an introduction and agenda for a course on big data and data science. It defines big data as large, complex data sets that are difficult to process using traditional data processing applications. It notes that 90% of data in the world today was created in the last two years alone. It also defines the four V's of big data: volume, variety, velocity, and veracity. The document defines data science as an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. It notes that data scientists work with hypothesis generation, data analysis, and data visualization to gather insights that inform decisions. The document outlines some of the day-to-day responsibilities
Introduction to Data Mining and Data Warehousing
This document provides details about a course on data mining and data warehousing. The course objectives are to understand the foundational principles and techniques of data mining and data warehousing. The course description covers topics like data preprocessing, classification, association analysis, cluster analysis, and data warehouses. The course is divided into 10 units that cover concepts and algorithms for data mining techniques. Practical exercises are included to apply techniques to real-world data problems.
Linguistic Cues to Deception: Identifying Political Trolls on Social Media
The document summarizes research on identifying political trolls on social media through their linguistic cues of deception. Key findings include:
- Russian trolls active in the 2016 US election aimed to sow discord by discussing divisive topics like Trump, police, and race on Twitter.
- Analyses found trolls used more deceptive language through increased uncertainty, less self-reference, and shorter, less complex tweets than non-trolls.
- Machine learning classifiers could predict trolls with over 80% accuracy based on their deceptive linguistic patterns, showing the potential to automatically detect political trolls online.
The Emergence Of Social Bots In Social Media- WiDS Talk
Social bots are algorithms that automatically produce content and interact with humans on social media to emulate and potentially manipulate human behavior. Around 9-15% of active Twitter accounts may be bots. Bots are used for marketing, entertainment, gaining followers, spamming, influencing opinions, and limiting free speech. About 30% of users can be deceived by bots. Identifying bots can be difficult as sophisticated bots mimic human behavior, but graph-based and feature-based methods analyze social networks and individual account features to detect bots with machine learning classifiers. The arms race between bot detection and deception will continue as long as deception remains effective.
More Related Content
Similar to Machine learning_snap#3
antrikshindutrialmachinelearningPPT.pptx
This document provides an overview of machine learning and data science using Python. It introduces machine learning and data science, the Python programming language, popular integrated development environments for Python, and Google Colab. It also discusses types of machine learning algorithms, the machine learning process, important Python libraries, the data science life cycle, data visualization techniques, and the differences between machine learning and data science. The document outlines how to use Google Colab for machine learning and data science projects and provides information on the scope and applications of machine learning and data science.
Basics of Intelligent Computing.pdf
This document provides an overview of the IT201 Basics of Intelligent Computing course. It outlines the course outcomes, which include being able to distinguish AI branches, solve problems using techniques like fuzzy logic and genetic algorithms, design neural networks, and discuss cloud computing and IoT. It also describes the various modules that make up the course, including introductions to computing, intelligent computing, and artificial intelligence concepts. Specific techniques discussed for solving AI problems include search, use of knowledge, and abstraction. The document provides examples of different programming approaches for problems like tic-tac-toe and question answering.
Showcasing research data tools - Jisc Digifest 2016
The document summarizes several projects from Phase 3 of the Research Data Spring initiative. It describes DataVault, a platform for long-term archival of research data. It also discusses DMA Online, a dashboard that aggregates research data management information from multiple sources. Additionally, it outlines Clipper, a tool for creating and sharing clips from audiovisual materials. Finally, it presents a project that aims to incentivize data deposit by enabling researchers to publish "data papers" describing their datasets.
Showcasing research data tools
Demo at DigiFest 2016 on 4 of the research data spring funded projects that address research data management issues.
Software Mining and Software Datasets
This document discusses software mining and datasets. It begins by introducing Tao Xie and his research group at the University of Illinois which focuses on software analytics. It then discusses different types of software services and data, how data has become more pervasive, and challenges in making repositories more actionable. Key topics in software analytics research are discussed including the goal of enabling insights for practitioners. Examples of mined information from different repository types like source code, bug reports, and mailing lists are provided.
Data Science at Scale - The DevOps Approach
DevOps Practices for Data Scientists and Engineers
1 Data Science Landscape
2 Process and Flow
3 The Data
4 Data Science Toolkit
5 Cloud Computing Solutions
6 The rise of DevOps
7 Reusable Assets and Practices
8 Skills Development
Datat and donuts: how to write a data management plan
This document provides guidance on how to write a data management plan (DMP). It discusses what a DMP is, why researchers should care about data management, and where data management fits into the research cycle. It also covers the key components of a successful DMP, including a data inventory, a strategy for describing the data, a plan for long-term data preservation, and methods for making the data accessible. The document provides examples and exercises to help researchers develop the sections of a DMP for their own research projects.
Simbios - Open Science in Biocomputational Research
Presentation on the Simbios National Center for Biomedical Computing and our efforts to promote open source and open data within the biocomputational research community. Presented at the Stanford Open Source Lab (un)Conference, November 2008
The Ai & I at Work
The document provides a history of data science and artificial intelligence, discusses how the two fields intersect, and provides examples of practical coding techniques for data scientists using AI tools. It begins with a brief history of data science from the 1960s development of empirical data analysis to the modern role of data scientists. It then discusses the parallel history of AI from its origins in the 1950s to recent advances in deep learning. The document explains that data scientists today can focus on analysis or building machine learning models, and that Python is a common coding language in both fields. It offers Jupyter Notebooks, Google Collab, and Docker as tools and provides examples using sentiment analysis, Google AutoML, and AWS DeepLens.
AI and Healthcare: An Overview (January 2024)
Use this presentation to:
- learn about the historical roots of AI
- learn about major events in the AI timeline
- get an overview of some of the ways that AI is being used now in healthcare to facilitate provider-patient communication, mine medical records, assess patients, predict illness, suggest treatments, enable patient monitoring
This presentation is updated for early 2024 and addresses AI's use in the creation of dis/misinformation and deepfakes, as well as the bias inherent in AI, brought on by the data sets used to train it.
00-01 DSnDA.pdf
The document discusses the growth of data and the field of data science. It begins by noting the large amounts of data being generated daily by various sources like web/e-commerce transactions, social networks, and scientific projects. It then discusses some of the challenges of big data including volume, velocity, and variety. The document provides an overview of the multidisciplinary nature of data science and the skills required of data scientists. It also summarizes different approaches to and job roles in data science.
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
AI is the new ELECTRICITY - said Andrew Ng. There are two sides of the coin. There are a lot of nay-sayers for AI. At the end of the day, it will be Augmented Intelligence, Adaptive Intelligence, Automated Intelligence that will propel human intelligence forward - more than anything else. It will be a great time ahead. Whether it would be an "Eye(AI) Wash" as skeptics say or an "I wish" from them for starting late on the journey, only time will tell. It is a matter of when and how long, instead of an If. #ArtificialIntelligence #IntelligentTesting #QCoE #NextGenTesting #QualityFocusedDelivery #DigitalInnovation #ITIndustry #NewAgeIT #InnovativeTesting#AIFication #Automation #DigitalEconomy #Singularity #Transcendence #Futurism
Webinar: Machine Learning para Microcontroladores
Neste webinar, serão apresentados conceitos sobre inteligência artificial, assim como ferramentas disponíveis para o desenvolvimento integradas ao MPLAB X e ao Harmony 3 e demonstração de um sistema de detecção de anomalia utilizando um microcontrolador da família ATSAMD21 (ARM Cortex M0+).
Biostast
The document discusses the basics of computational biology and computer components. It defines computational biology as being hypothesis-driven and involving using mathematical modeling and simulation to study biological systems, giving modeling gene regulatory networks as an example. It also defines bioinformatics as being data-driven and involving using computational tools to analyze biological data, such as protein database searching. The document then provides basic information about computer components like memory types, CPU parts, and differences between primary and secondary memory.
Smarter Data for Smarter Libraries
This document discusses how libraries can leverage data from their collections to support new research and discovery. It outlines several initiatives that treat library collections as data, including the Library of Congress labs and a project exploring computationally-driven research. The document also discusses OCLC's work analyzing institutional repository data through its Repository Analytics and Metrics Portal (RAMP) and making data more interoperable through support of the IIIF standard for sharing images and metadata.
Intro to RDM
An introduction to Research Data Management and Data Sharing given via webinar for Diponegoro University, Indonesia
Elixir at de.nbi meeting
- Data transfer
- Compute access
- Training
Data Hub:
- Secure data sharing
- Data management
- Metadata catalogues
AAI:
- Single sign-on
- User attributes
- Group management
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
National
resources
intelligentsystems-140424154432-phpapp01.pptx
This document provides an overview of intelligent systems (IS). It begins with defining three main categories of IS: industrial, household, and research. Several examples are given for each category, such as autonomous vehicles for industry, personal assistants like Siri for households, and nursing robots for research. The document then discusses major IS research centers around the world and some notable people and publications in the field of IS.
Introduction to Big Data and Data Science
The document provides an introduction and agenda for a course on big data and data science. It defines big data as large, complex data sets that are difficult to process using traditional data processing applications. It notes that 90% of data in the world today was created in the last two years alone. It also defines the four V's of big data: volume, variety, velocity, and veracity. The document defines data science as an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. It notes that data scientists work with hypothesis generation, data analysis, and data visualization to gather insights that inform decisions. The document outlines some of the day-to-day responsibilities
Introduction to Data Mining and Data Warehousing
This document provides details about a course on data mining and data warehousing. The course objectives are to understand the foundational principles and techniques of data mining and data warehousing. The course description covers topics like data preprocessing, classification, association analysis, cluster analysis, and data warehouses. The course is divided into 10 units that cover concepts and algorithms for data mining techniques. Practical exercises are included to apply techniques to real-world data problems.
Similar to Machine learning_snap#3 (20)
Showcasing research data tools - Jisc Digifest 2016
Showcasing research data tools - Jisc Digifest 2016
Datat and donuts: how to write a data management plan
Datat and donuts: how to write a data management plan
Simbios - Open Science in Biocomputational Research
Simbios - Open Science in Biocomputational Research
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
Artificial Intelligence in testing - A STeP-IN Evening Talk Session Speech by...
More from Aseel Addawood
Linguistic Cues to Deception: Identifying Political Trolls on Social Media
The document summarizes research on identifying political trolls on social media through their linguistic cues of deception. Key findings include:
- Russian trolls active in the 2016 US election aimed to sow discord by discussing divisive topics like Trump, police, and race on Twitter.
- Analyses found trolls used more deceptive language through increased uncertainty, less self-reference, and shorter, less complex tweets than non-trolls.
- Machine learning classifiers could predict trolls with over 80% accuracy based on their deceptive linguistic patterns, showing the potential to automatically detect political trolls online.
The Emergence Of Social Bots In Social Media- WiDS Talk
Social bots are algorithms that automatically produce content and interact with humans on social media to emulate and potentially manipulate human behavior. Around 9-15% of active Twitter accounts may be bots. Bots are used for marketing, entertainment, gaining followers, spamming, influencing opinions, and limiting free speech. About 30% of users can be deceived by bots. Identifying bots can be difficult as sophisticated bots mimic human behavior, but graph-based and feature-based methods analyze social networks and individual account features to detect bots with machine learning classifiers. The arms race between bot detection and deception will continue as long as deception remains effective.
معالجة اللغة الطبيعية
The document discusses natural language processing (NLP) and some of its applications. NLP is a field of computer science concerned with interactions between computers and human languages. Some key applications discussed include question answering, information extraction from texts and emails, machine translation, text summarization, sentiment analysis, and context analysis. Examples of each application are provided. The document also provides information about setting up an environment for exploring an Arabic sentiment analysis task using NLP.
Data Science Workshop - day 1
This workshop was presented in Riyadh, SA in 21-22 Jan 2019, with the collaboration with Riyadh Data Geeks group.
To learn more about the workshop please see this website:
http://bit.ly/2Ucjmm5
Data Science Workshop - day 2
This workshop was presented in Riyadh, SA in 21-22 Jan 2019, with the collaboration with Riyadh Data Geeks group.
To learn more about the workshop please see this website:
http://bit.ly/2Ucjmm5
Data Science Workflow
This document outlines the typical steps for conducting a data science project:
1. Identify the problem and research questions
2. Collect and store relevant data
3. Annotate and extract features from the data
4. Clean the data by preprocessing and handling missing values
5. Explore and analyze the data using descriptive statistics and plots
6. Train machine learning classification models on the data
7. Assess the models, communicate the results through visualization, applications, and reports
Data discrimination and bias snap #6
تحيز البيانات
These slides are linked to the Snapchat account data_sci
https://sites.google.com/view/data-sci
Data Visualization snap#5
Data visualization is the visual representation of data to help understand patterns and insights more easily. Some common types of data visualizations include charts, graphs, maps and infographics. Effective data visualization helps tell stories with data in a way that is easy to understand and share with others.
Data storytelling_snap#4
Data storytelling is a method of delivering messages derived from complex data analysis in a way that allows audiences to quickly understand its meaning and draw conclusions. It uses key ingredients like narrative, visuals, and data, with data being the foundation. Narratives present connected events in sequence, while visual communication shows viewers relationships they cannot see in data alone, allowing exploration and understanding.
Data science Snap#2
Data science can be learned without a PhD by developing a T-shaped skill set of both broad interdisciplinary knowledge and expertise in one or more areas. The document recommends gaining hands-on experience with data science projects as the best way to learn, rather than just theoretical study. Developing a T-shaped skill set through practical experience with data science projects allows one to learn data science effectively.
Data science Snap1
The document discusses data science and what can be done with data. It notes that data comes from many sources and is everywhere. Some potential uses of data include recommender systems, image recognition, digital advertisements, speech recognition, gaming, price comparison websites, airline route planning, fraud and risk detection, and delivery logistics. The document also references two URLs about what data is and the data science process.
More from Aseel Addawood (11)
Linguistic Cues to Deception: Identifying Political Trolls on Social Media
Linguistic Cues to Deception: Identifying Political Trolls on Social Media
The Emergence Of Social Bots In Social Media- WiDS Talk
The Emergence Of Social Bots In Social Media- WiDS Talk
Recently uploaded
sim owner details | +447490809237 | sim owner details pakistan
Whatsapp Number: +447490809237
sim owner details
sim owner details pakistan
nadra sim owner details
sim owner details by number
sim owner details online
sim owner details apk
sim owner details app
sim owner details online check pakistan
pak sim data sim owner details
zong sim owner details
check sim owner details
how to check sim owner details in pakistan
find sim owner details in pakistan
mobile sim owner details
how to check sim owner details
sim card owner details
sim card owner details online
sim owner details with name and address
track sim card owner details online
jio sim owner details
sim owner details software
check sim card owner details
find sim owner details
how to check airtel sim owner details
how to check sim card owner details
how to find a sim owner details
how to find sim owner details
how to know sim card owner details
how to know sim owner details
idea sim card owner details online
sim card owner details app
sim card owner details software
sim owner name details
ufone sim owner details
00923456435194 sim owner detail
ap to know the sim owners details
check sim number owner details
find out details of owner of sim card
finding sim registration owner details
full details of sim card owner pakistan
how to check my sim owner details
how to check owner detail through sim
how to check owner details of a sim
how to check owner details of jaz sim
how to check sim owner details who tease people
how to check sim owner name and detail warid
how to chek owner details of sim
how to find a sim owner details pakista
how to find a sim owner details pakistan
how to find sim card owner details in pakistan
how to get details of others sim owner in pakistan
how to trace a sim owner details pakistan
idea sim card owner details
iran sim details of owner
iran sim details of owner website
mobile phone number details sim owner name address
mobile phone number details sim owner name address location
online sim owner details.pakistan
pakistan prepaid sim owner details
pakistan sim owner details
phone number details sim owner name address location
search sim card owner and details using apk
sim card owner details app for pakistan
sim detail check online owner
sim details online by number owner name
sim number all details with owner name
sim number all details with owner name id card
sim owner call details online
sim owner details by contact number
sim owner details online with name and address
sim owner name full details
Check SIM Owner Details | +447490809237 | Sim Details in Pakistan
Whatsapp Number for Paid Service:
+447490809237
How To Check SIM Owner Name And CNIC Of Any Mobile Number
Thanks to the Pakistan Telecommunication Authority’s (PTA) online verification facilities, obtaining SIM owner information has become much easier. Here’s how to find the CNIC and SIM owner details by number:
Compose an SMS to 667: Open a new message on your SIM card and write “MNP”.
Send the SMS: Send this message to the shortcode 667.
Receive Information: Wait for a reply. A message containing the name of the SIM owner associated with the specific SIM number will be sent to you.
Additionally, you can visit or call your network service provider’s local customer care center to confirm the SIM registration status and owner’s name. This simplified procedure eliminates the need for extensive documentation and offers a convenient way to obtain necessary SIM details in Pakistan.
Check SIM Owner Details With Name Online
In Pakistan, there are various Android apps and software solutions available to check the SIM owner’s name by mobile number online. However, it is important to note that most of these apps have not been approved by the Pakistan Telecommunication Authority (PTA), and their use is not recommended. If you choose to use these apps, proceed with caution. Remember, the current law only permits the registration of five SIMs under one identity.
Always verify the validity of any software or tool you decide to use, as unauthorized access to SIM owner credentials may have legal consequences.
Check Jazz SIM Owner Name Details 2024
To check Jazz SIM owner name and details online, follow these steps:
Open the Messaging App: On your mobile phone, open the messaging app.
Create a New Message: Type “667” in the recipient field.
Write the Message: Type “MNP” in the message body.
Send the Message: Send the message using your Jazz SIM.
Wait for a Response: You will receive a message containing the SIM owner’s name and CNIC number associated with the Jazz SIM you are using.
Terms:
Codes can change at any time. Check the Jazz website if the code above has an error.
For further information, call the Jazz helpline.
You can check the Jazz SIM owner, registered address, and location by calling the helpline.
Check Ufone Sim Owner Name Details 2024.
If you want to Check Ufone SIM Owner Name & Ufone SIM Owner Details online check it by the following steps:
Open the messaging app on your mobile phone.
Create a new message.
In the recipient field, type “667”.
In the message body, type “MNP”.
Send the message through your Ufone SIM.
Wait for a response. You will receive a message containing the SIM owner’s name and CNIC number associated with the Ufone SIM which is in your use.
#sim owner details
#sim owner details pakistan
#nadra sim owner details
#sim owner details by number
#sim owner details online
#sim owner details apk
#sim owner details app
#sim owner details online check pakistan
#pak sim data sim owner details
#zong sim owner details
How to Handle Open Web Application Security Project(OWASP) Top Vulnerabilities
Handling OWASP top vulnerabilities requires a proactive and multi-faceted approach. It involves implementing secure coding practices, regular security assessments, and staying up-to-date with the latest security trends and patches. By fostering a security-first mindset and integrating security into the development lifecycle, organizations can significantly reduce the risks posed by these common vulnerabilities.
To get more information, check
https://whitecoastsecurity.com/safeguarding-web-applications-a-white-coast-security-perspective-on-the-owasp-top-10-vulnerabilities/
#1 Call Girls in Islamabad || 03274100048 || Quick Booking at Affordable Price
Islamabad Call Girls Services – Available 24/7
One of the most educated and reliable Call Girls in Islamabad. They only work with real guys who want to enjoy the company of our high-class, sexy call girls with love and respect. Our call girls have enough experience to know how to make their guests happy at that time. Of course, we’re known for our genuine hospitality.
Our stylish Independent Islamabad call girls are available 24 hours a day, seven days a week. People who work for our agency will make you feel right at home as soon as you meet them. You’ll feel like you’re at a real Call Girl agency in Islamabad.
Our guests come back repeatedly, and no matter what megacity they visit, they always contact us to talk about the nightlife. If you’re in a big city by yourself and getting sexy in a hotel room. Our girls are so well-trained that they can go to a club, a party, or a DJ night with you and make you feel unforgettable.
Our VIP call girls are dedicated to their jobs and look forward to giving you a great experience and ensuring you’re delighted. We are quick at getting new gifts, which is why our customers love us so much. Before, you saw our girls’ portfolios and hot pictures, which made you want to do anything. Book your stay in Islamabad right now by calling.
Special Moments with Islamabad Call Girls
Customers are surprised by how satisfying, inspiring, and powerful Islamabad Call Girl’s minutes are, which makes them love her even more. Our agency’s name in the market is due to our excellent call girls, who keep clients coming back for life.
As a Call Girl service in Islamabad, Islamabad Nights Call Girl has been helping a wide range of clients for a long time. His work makes the value of the business easy to understand, appealing, and beautiful. The only thing that makes the firm successful is its dedication to giving clients excellent customer service.
The terms and conditions of the Islamabad Call Girls service are standard. Kids under 18 can’t get help from this government because it doesn’t want them; they have to be at least 18 years old. His agency only gives the power to mature people travelling with real sidekicks.
The people who work for this office are trained, responsible, and prepared for their jobs. They don’t like other Call Girls who only want money in exchange for giving clients beds. They serve both inside and outside people.
Ready to Meet Islamabad Call Girls Now!
You don’t need to wait. We’ll send hot Call Girls to your house if you call us. It’s easy for these young, pretty women to make guys happy.
No need to worry about how they treat you because they are all very friendly and work for a company. They know how to make every guy happy.
#call girls in islamabad #islamabad call girls #call girl in islamabad #islamabad call girl
Material Testing Lab Services in Dubai.pptx
Dubai is home to numerous advanced material testing labs, offering state-of-the-art facilities for a wide range of industries. These labs provide critical services such as mechanical testing, chemical analysis, and non-destructive testing, ensuring the quality and durability of materials used in construction, aerospace, and manufacturing.
OpenText Vulnerability Assessment & Penetration Testing
An OpenText™ Vulnerability Assessment provides organizations with a thorough understanding of the weaknesses and potential risks in their applications, systems, and networks. Armed with this insight, they can address vulnerabilities, enhance their cybersecurity defenses, and ensure compliance with insurance and regulatory requirements.
How Can I Apply in India (2024) for a US B1/B2 Visa Renewal?
Are your US visas current? Though it will soon expire, I’m not sure what to do. We will assist you in getting a fresh US visa and being protected. The procedures and conditions for renewing a US B1/B2 visa can grab your attention. This blog article will cover everything you need to know regarding the US B1/B2 visa renewal in India in 2024. Alternatively, do you have to show up for an interview? Right now, the US B1/B2 visa waiting period in India is what?
Foresic Academy. Information Security Company in Punjab (INDIA)
Forensic Academy follows a broad vision of defending information from unauthorized access, use , disclosure,
disruption, modification, perusal, inspection, recording or destruction. The aim at Forensic Academy is to
provide information security solutions to clients with wide line-up of platforms: network, web application,
Android or IOS Application, Servers, Cloud and databases. Forensic Academy provides practical and interactive
training on Ethical hacking covering various subjects in information security and has structured customized
certification courses covering needs of newbies', students and corporate world- Forensic Academy aims to
cater to the need of all.
FORENSIC ACADEMY has a larger aim of expanding the IT Security which is not more that 10 years old in
INDIA. India has not more than 1000 cyber security experts which are quite less compared to the requirement
of more than 4 lakh experts. Increase in worldwide awareness in cyber security demands a growth in India
too.
一比一原版（UWA毕业证）西澳大学毕业证如何办理
原件一模一样【微信：176555708】【西澳大学毕业证（UWA学位证）成绩单】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：176555708】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理西澳大学毕业证（UWA学位证）学位证【微信：176555708 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理西澳大学毕业证（UWA学位证）学位证【微信：176555708 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理西澳大学毕业证（UWA学位证）学位证【微信：176555708 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理西澳大学毕业证（UWA学位证）学位证【微信：176555708 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Solar powered Security Camera- Sun In One
Solar Power Kit for a CCTV system involves selecting and integrating several components to ensure reliable power for your surveillance setup.
How Does Fantasy Sports Mobile App Make Money?
Looking to develop a fantasy sports app of your own, IMG Global Infotech is a leading fantasy app development company with a proven track record of success. Our team of experts can help you bring your vision to life and create a profitable fantasy sports app. Contact IMG Global Infotech today.
https://www.imgglobalinfotech.com/fantasy-sports-app-development.php
Generate Revenue with Contact Center Business Model Strategy
Transform your contact center business model into a revenue-generating powerhouse with strategic insights and operational excellence.
Findlay Evans Waterproofing with AIW - Article November 2019
Findlay Evans Waterproofing with AIW - Article November 2019MELBOURNE Commercial Waterproofers - Findlay-Evans Waterproofing
Floor Waste Requirements for Bathrooms in Australia
Waterproofing Melbourne and the entire construction industry must stay updated with the latest amendments to the Australian Standard AS3740 and the National Construction Code (NCC). Recent changes emphasize floor waste requirements and fall requirements in bathrooms, which are crucial for maintaining high standards of commercial waterproofing and other waterproofing practices.
Scope
The amendments clarify the waterproofing of wet areas within residential buildings across various states, including New South Wales, Queensland, and Western Australia. The NCC, a performance-based code, includes Volumes 1 and 2 (Building Code of Australia) and Volume 3 (Plumbing Code of Australia).
Legislation Overview
The NCC provides the minimum necessary standards for safety, health, sustainability, and amenity in building and plumbing legislation across Australia. It is divided into performance requirements and allows for compliance through Deemed-to-Satisfy Provisions or alternative solutions.
BCA Volume 1
F1.7 Waterproofing of Wet Areas: Ensures wet areas in buildings are adequately waterproofed to prevent damage and maintain safety.
F1.11 Floor Grading: In Class 2 or 3 buildings or Class 4 parts of a building, bathroom or laundry floors located above a sole occupancy unit or public space must be graded to prevent water spillage.
BCA Volume 2
Performance Requirement P2.4.1: Addresses waterproofing of wet areas in Class 1 and 10 buildings, specifying that these areas must meet specific performance criteria to ensure effective waterproofing.
Floor Waste and Grading Requirements
The NCC Volume 1 and 2, along with the Australian Standard, provide performance requirements for waterproofing elements in wet areas. However, the BCA Volume 2 does not mandate floor waste installation in Class 1 buildings, such as single dwelling houses, except for rooms with wall-hung urinals. The floor in these buildings does not need to be graded to a floor waste gully, even if one is present.
In contrast, Class 2, 3, or 4 buildings with bathrooms or laundries located above other sole occupancy units or public spaces require floor waste installations to prevent water from entering the spaces below. The floors in these areas must be graded to the floor waste.
Importance of Compliance
Compliance with these standards is critical for preventing waterproofing failures, which can lead to significant post-construction issues, including structural damage and health hazards. Ensuring proper waterproofing in areas like basement waterproofing, retaining wall waterproofing, and lift pit waterproofing is essential for the longevity and safety of buildings.
The Role of Training and Education
Paul Evans highlights the importance of ongoing training and education in the waterproofing industry. By staying informed about legislative changes and best practices, professionals can improve the quality of their work and reduce the risk of defects. Findlay Evans Waterproofing with AIW - Article April 2017
Findlay Evans Waterproofing with AIW - Article April 2017MELBOURNE Commercial Waterproofers - Findlay-Evans Waterproofing
The AIW Delivers on the Importance of Waterproofing
On March 29, 2017, the AIW attended and presented at the ADEB (Architects Designers Engineers Builders) Waterproofing Breakfast Seminar in Sydney. The focus was on addressing commercial waterproofing and residential high-rise waterproofing failures and solutions.
Presentations and Key Points
Paul Evans, AIW President, gave an overview of the AIW's role in raising waterproofing standards in Australia. Robert McDonald, an AIW member, delivered a session on the “Australian Standards in Waterproofing.” These presentations covered:
Common defects in internal and external waterproofing
Priming and substrate moisture content
Inspection and testing of waterproofing
Drainage and waterproofing techniques
Product knowledge and standards compliance, including:
CA 55 - 1970 (Design and Installation of Bituminous Fabric Roofing)
AS 3740 (Waterproofing Wet Areas in Residential Buildings)
AS 4858 - 2004 (Wet Area Membranes)
AS 4654 - 2012 (Waterproofing Membrane)
The AIW remains dedicated to updating, providing current information, and educational resources for all industries involved with waterproofing.
Achieving Uniform Waterproofing Compliance Nationally
Achieving uniform waterproofing compliance across Australia involves collaboration with State and Territory Regulatory Authorities, which play a crucial role. Current licensing requirements are often disjointed, and in many states, not mandatory.
Local authorities and building surveyors request Waterproofing Application Certificates to certify compliance with BCA and Australian Standards. These certificates must be issued by a competent person, whose work falls under the scope of their license or who has formal qualifications to carry out the work. Training and qualifications are regulated under the National Qualifications Framework.Findlay Evans Waterproofing with AIW - Article October 2018
Findlay Evans Waterproofing with AIW - Article October 2018MELBOURNE Commercial Waterproofers - Findlay-Evans Waterproofing
The construction industry is undergoing significant changes, particularly in waterproofing. Poor practices have caught the attention of regulators, and changes are coming soon. AIW will keep members informed about these developments. We aim to eliminate subpar contractors who compromise the industry with inadequate work.
Everyone makes mistakes occasionally, but persistent issues arise from those who consistently cut corners, using insufficient materials in unsafe conditions. These practices must end.
Summer Waterproofing Challenges
As summer approaches, common questions arise regarding membrane application in hot or humid conditions:
Is it too hot or humid to apply a membrane?
Will blistering occur?
How to address blistering if it happens?
Should a warranty be issued for such membranes?
Applying membranes in inappropriate conditions often leads to failures. It’s crucial to consider the long-term repercussions of these decisions. Consult your membrane supplier for guidance and ensure you ask the right questions. Industry peers are often willing to help.
Project Reference: QLD Public Hospital
Overview
Property Type: QLD Public Hospital
Contractor/Applicator: Waterstop Solutions
Testing: International Leak Detection Australia (ILD)
Category: Membrane Renewal
Products Used: A specialized bitumen-modified highly flexible waterproofing membrane installed in multiple layers over a moisture barrier primer system.
Project Details: The project involved renewing the waterproofing membrane on two leaking concrete tanks, critical for the hospital’s fire sprinkling system. Challenges included identifying all leaks and adhering to noise and downtime restrictions. The solution involved thorough surface preparation and the use of a compatible, highly flexible membrane, ensuring long-term effectiveness and compliance with Australian Standards.
AIW at Bayset Construction Trade Day
On August 24, 2018, AIW attended the Bayset Construction Trade Day at Coopers Plains Branch. The event was a great opportunity to connect with members and non-members, resulting in increased interest and new sign-ups. The day featured informative sessions, industry support, and excellent networking opportunities.#1 Call Girls in Mumbai || +919004268417 || Quick Booking at Affordable Price
#1 Call Girls in Mumbai || +919004268417 || Quick Booking at Affordable Price
How our Rebranding Succeeds in Instilling trust in Every Agri Citizen
Ninjacart recently rebranded to emphasize its mission of improving the lives of agri citizens, including farmers, traders, and retailers. The rebranding introduced affiliated brands NinjaMandi, NinjaGlobal, NinjaKirana, and NinjaKisan, expanding Ninjacart's offerings to credit and commerce. A new brand film honors the contributions of agri citizens, fostering pride and trust among customers. The updated logo symbolizes Ninjacart's commitment to unity and growth in the agri value chain. This transformation highlights Ninjacart’s evolution from a fulfilment-centric business to a comprehensive marketplace platform, aiming to build #BetterLives for all agri citizens.
The best Social Media Spy Apps for Catching Your Unfaithful Wife.pdf
Do you want to Monitor your Partner's Social media?
The 5 Most Important Pipefitter Tools.pdf
Equip yourself with the essential tools every pipefitter needs to tackle any job with confidence. "The 5 Most Important Pipefitter Tools" explores the must-have instruments that form the backbone of a pipefitter's toolkit. From pipe wrenches and tube cutters to threading machines and alignment clamps, this guide provides an in-depth look at the key tools that ensure precision and efficiency in every project. Learn about the functions, features, and benefits of each tool, along with expert tips on how to use them effectively.Whether you're a seasoned professional or an aspiring pipefitter, understanding these fundamental tools is crucial for success in the field. Discover how investing in the right equipment can enhance your craftsmanship and productivity in pipefitting tasks.
QuickBooks Unrecoverable Error...........
In the realm of accounting software, QuickBooks stands as a cornerstone for businesses of various sizes. Its robust features streamline financial operations, offering efficiency and accuracy in managing accounts, payroll, invoices, and more. However, like any complex software system, QuickBooks is not immune to errors. Among the most vexing issues users encounter is the "QuickBooks Unrecoverable Error." This error can halt productivity, disrupt workflow, and leave users scrambling for solutions.
Recently uploaded (20)
sim owner details | +447490809237 | sim owner details pakistan
sim owner details | +447490809237 | sim owner details pakistan
Check SIM Owner Details | +447490809237 | Sim Details in Pakistan
Check SIM Owner Details | +447490809237 | Sim Details in Pakistan
How to Handle Open Web Application Security Project(OWASP) Top Vulnerabilities
How to Handle Open Web Application Security Project(OWASP) Top Vulnerabilities
#1 Call Girls in Islamabad || 03274100048 || Quick Booking at Affordable Price
#1 Call Girls in Islamabad || 03274100048 || Quick Booking at Affordable Price
OpenText Vulnerability Assessment & Penetration Testing
OpenText Vulnerability Assessment & Penetration Testing
How Can I Apply in India (2024) for a US B1/B2 Visa Renewal?
How Can I Apply in India (2024) for a US B1/B2 Visa Renewal?
Foresic Academy. Information Security Company in Punjab (INDIA)
Foresic Academy. Information Security Company in Punjab (INDIA)
Generate Revenue with Contact Center Business Model Strategy
Generate Revenue with Contact Center Business Model Strategy
Findlay Evans Waterproofing with AIW - Article November 2019
Findlay Evans Waterproofing with AIW - Article November 2019
Findlay Evans Waterproofing with AIW - Article April 2017
Findlay Evans Waterproofing with AIW - Article April 2017
Findlay Evans Waterproofing with AIW - Article October 2018
Findlay Evans Waterproofing with AIW - Article October 2018
#1 Call Girls in Mumbai || +919004268417 || Quick Booking at Affordable Price
#1 Call Girls in Mumbai || +919004268417 || Quick Booking at Affordable Price
How our Rebranding Succeeds in Instilling trust in Every Agri Citizen
How our Rebranding Succeeds in Instilling trust in Every Agri Citizen
The best Social Media Spy Apps for Catching Your Unfaithful Wife.pdf
The best Social Media Spy Apps for Catching Your Unfaithful Wife.pdf
Machine learning_snap#3
- 2. Machine Learning and AI AI Machine Learning
- 4. Machine learning is all about finding patterns in data
- 5. Traditional Programming Machine Learning Computer Data Program Output Computer Data Output Program
- 6. Machine learning is about predicting the future based on the past -- Hal Daume III
- 7. Machine Learning and Data Science Machine Learning
- 8. Why Machine Learning? 1. No human experts 2. Black-box human expertise 3. Rapidly changing phenomena • Need for customization/personalization
- 9. Resources
- 10. Technical Papers Journals: • Machine Learning. • Journal of Machine Learning Research. • IEEE Transactions on Neural Networks. • IEEE Transactions on Pattern Analysis and Machine Intelligence. • Journal of the American Statistical Association. Conferences: • International Conference on Machine Learning (ICML) • Neural Information Processing Systems (NIPS)
- 11. 11 Datasets • UCI Repository: http://www.ics.uci.edu/~mlearn/MLRepository.html • UCI KDD Archive: http://kdd.ics.uci.edu/summary.data.application.html • Statlib: http://lib.stat.cmu.edu/ • Delve: http://www.cs.utoronto.ca/~delve/
- 12. References • AAAI. Machine Learning. http://www.aaai.org/Pathfinder/html/machine.html • Dietterich, T. (2003). Machine Learning. Nature Encyclopedia of Cognitive Science. • Doyle, P. Machine Learning. http://www.cs.dartmouth.edu/~brd/Teaching/AI/Lectures/Summaries/learning.html • Dyer, C. (2004). Machine Learning. http://www.cs.wisc.edu/~dyer/cs540/notes/learning.html • Mitchell, T. (1997). Machine Learning. • Nilsson, N. (2004). Introduction to Machine Learning. http://robotics.stanford.edu/people/nilsson/mlbook.html • Russell, S. (1997). Machine Learning. Handbook of Perception and Cognition, Vol. 14, Chap. 4. • Russell, S. (2002). Artificial Intelligence: A Modern Approach, Chap. 18-20. http://aima.cs.berkeley.edu