Is deep learning just a marketing buzzword? What is it used for? And how can you get started?
5 min lightning talk presented at PyLadies/Women Who Code
Es una presentaciĂłn que abarca los fundamentos de la tecnologĂa como son las tics, paginas web, portales, medios de comunicaciĂłn y el uso adecuado que se les debe dar.
Week 1
Descriptive statistics (graded)
If you were given a significant knowledge set such as the income over the last 12 months of our high 1,000 purchasers, what would you be able to do with this data? What probably the advantages of describing the information?
Week 2
Regression (graded)
feel you might be given information from a survey displaying the IQ of every character interviewed and the IQ of his or her mother. That is all the information that you have. Your boss has requested you to put collectively a document showing the relationship between these two variables. What would you gift and why? Continue Reading Please Visit Our Website.
Es una presentaciĂłn que abarca los fundamentos de la tecnologĂa como son las tics, paginas web, portales, medios de comunicaciĂłn y el uso adecuado que se les debe dar.
Week 1
Descriptive statistics (graded)
If you were given a significant knowledge set such as the income over the last 12 months of our high 1,000 purchasers, what would you be able to do with this data? What probably the advantages of describing the information?
Week 2
Regression (graded)
feel you might be given information from a survey displaying the IQ of every character interviewed and the IQ of his or her mother. That is all the information that you have. Your boss has requested you to put collectively a document showing the relationship between these two variables. What would you gift and why? Continue Reading Please Visit Our Website.
Inside Deep Learning: theory and practice of modern deep learningManning Publications
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Inside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain English.
Learn more about the book here: http://mng.bz/MXyE
Machine Learning and its subsequent fields have undergone tremendous growth in the past few years. It has a number of potential applications and is being used in different fields...
IgmGuru takes great pride in introducing the well-curated deep learning with tensorflow training in which industry leaders and academia has been consulted while preparing this course.
IgmGuru takes great pride in introducing the well-curated Deep Learning with TensorFlow course in which industry leaders and academia has been consulted while preparing this course. IgmGuru is very enthusiastic about the Deep Learning with TensorFlow course as we will go through some of the famous use cases and prepare the learners to face industry-related challenges. Deep Learning is loosely inspired by the ways humans process information and then communicate through our own biological neural networks. These learning algorithms are able to process vast amounts of data to build meaningful relationships amongst them.
IgmGuru takes great pride in introducing the well-curated deep learning with tensorflow course in which industry leaders and academia has been consulted while preparing this course. IgmGuru is very enthusiastic about the Deep Learning with TensorFlow course as we will go through some of the famous use cases and prepare the learners to face industry-related challenges. Deep Learning is loosely inspired by the ways humans process information and then communicate through our own biological neural networks. These learning algorithms are able to process vast amounts of data to build meaningful relationships amongst them.
https://www.igmguru.com/machine-learning-ai/deep-learning-tensorflow-training/
This presentation attempts to explain some of the concepts used when describing data science, machine learning, and deep learning. IT also describes data science as a process, rather than as a set of specific tools and services.
This presentation targets people with a beginner background of Artificial Intelligence and Machine Learning, so anyone interested in understanding the working of the machine learning model and how to implement them in general is welcome to join us.
NYAI - Commodity Machine Learning & Beyond by Andreas MuellerRizwan Habib
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Commodity Machine Learning - (Andreas Mueller)
Recent years have seen a widespread adoption of machine learning in industry and academia, impacting diverse areas from advertisement to personal medicine. As more and more areas adopt machine learning and data science techniques, the question arises on how much expertise is needed to successfully apply machine learning, data science and statistics. Not every company can afford a data science team, and getting your PhD in biology, no-one can expect you to have PhD-level expertise in computer science and statistics.
This talk will summarize recent progress in automating machine learning and give an overview of the tools currently available. It will also point out areas where the ecosystem needs to improve in order to allow a wider access to inference using data science techniques. Finally we will point out some open problems regarding assumptions, and limitations of what can be automated.
Andreas is an Research Engineer at the NYU Center for Data Science, building open source software for data science. Previously, he worked as a Machine Learning Scientist at Amazon, developing solutions for computer vision and forecasting problems. He is one of the core developers of the scikit-learn machine learning library, and has co-maintained it for several years.
His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms.
In this Lunch & Learn session, Chirag Jain gives us a friendly & gentle introduction to Machine Learning & walks through High-Level Learning frameworks using Linear Classifiers.
Machine learning is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computer systems to learn and make predictions or decisions without being explicitly programmed. In essence, machine learning allows computers to automatically discover patterns, associations, and insights within data and use that knowledge to improve their performance on a task.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Inside Deep Learning: theory and practice of modern deep learningManning Publications
Â
Inside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain English.
Learn more about the book here: http://mng.bz/MXyE
Machine Learning and its subsequent fields have undergone tremendous growth in the past few years. It has a number of potential applications and is being used in different fields...
IgmGuru takes great pride in introducing the well-curated deep learning with tensorflow training in which industry leaders and academia has been consulted while preparing this course.
IgmGuru takes great pride in introducing the well-curated Deep Learning with TensorFlow course in which industry leaders and academia has been consulted while preparing this course. IgmGuru is very enthusiastic about the Deep Learning with TensorFlow course as we will go through some of the famous use cases and prepare the learners to face industry-related challenges. Deep Learning is loosely inspired by the ways humans process information and then communicate through our own biological neural networks. These learning algorithms are able to process vast amounts of data to build meaningful relationships amongst them.
IgmGuru takes great pride in introducing the well-curated deep learning with tensorflow course in which industry leaders and academia has been consulted while preparing this course. IgmGuru is very enthusiastic about the Deep Learning with TensorFlow course as we will go through some of the famous use cases and prepare the learners to face industry-related challenges. Deep Learning is loosely inspired by the ways humans process information and then communicate through our own biological neural networks. These learning algorithms are able to process vast amounts of data to build meaningful relationships amongst them.
https://www.igmguru.com/machine-learning-ai/deep-learning-tensorflow-training/
This presentation attempts to explain some of the concepts used when describing data science, machine learning, and deep learning. IT also describes data science as a process, rather than as a set of specific tools and services.
This presentation targets people with a beginner background of Artificial Intelligence and Machine Learning, so anyone interested in understanding the working of the machine learning model and how to implement them in general is welcome to join us.
NYAI - Commodity Machine Learning & Beyond by Andreas MuellerRizwan Habib
Â
Commodity Machine Learning - (Andreas Mueller)
Recent years have seen a widespread adoption of machine learning in industry and academia, impacting diverse areas from advertisement to personal medicine. As more and more areas adopt machine learning and data science techniques, the question arises on how much expertise is needed to successfully apply machine learning, data science and statistics. Not every company can afford a data science team, and getting your PhD in biology, no-one can expect you to have PhD-level expertise in computer science and statistics.
This talk will summarize recent progress in automating machine learning and give an overview of the tools currently available. It will also point out areas where the ecosystem needs to improve in order to allow a wider access to inference using data science techniques. Finally we will point out some open problems regarding assumptions, and limitations of what can be automated.
Andreas is an Research Engineer at the NYU Center for Data Science, building open source software for data science. Previously, he worked as a Machine Learning Scientist at Amazon, developing solutions for computer vision and forecasting problems. He is one of the core developers of the scikit-learn machine learning library, and has co-maintained it for several years.
His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms.
In this Lunch & Learn session, Chirag Jain gives us a friendly & gentle introduction to Machine Learning & walks through High-Level Learning frameworks using Linear Classifiers.
Machine learning is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computer systems to learn and make predictions or decisions without being explicitly programmed. In essence, machine learning allows computers to automatically discover patterns, associations, and insights within data and use that knowledge to improve their performance on a task.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Â
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
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Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
2. Are AI, ML, and Deep Learning synonyms?
Artificial
Intelligence
Deep
Learning
Machine
Learning
deep learning == many layer neural networks
No! Deep learning is a class of algorithms
Venn Diagram modified from
deeplearningbook.org
3. What can deep learning do?
Slides 3 and 4 inspired by Jeremy Howard
4.
5. Deep Learning is good at
reading and generating text
identifying and creating images
recognizing and interpreting speech
For more on this topic, watch The Wonderful and
Terrifying Implications of Computers that can Learn
6. An image is just a matrix of numbers
GIF from Adam Geitgey
8
7. How can you get started?
TensorFlow- (Python library from Google)
Tutorial for ML beginners
Learn linear algebra (vectors & matrices): Khan Academy
Get these slides/links: @math_rachel
Editor's Notes
Links:
Baidu’s Deep Speech 2
Gmail Smart Reply
NeuralStyle