Reinforcement Learning (59)

• Hands-On Reinforcement Learning Course, Part 2 - Dec 28, 2021.
  
  Continue your learning journey in Reinforcement Learning with this second of two part tutorial that covers the foundations of the technique with examples and Python code.

  Agents, Beginners, Python, Reinforcement Learning

• Hands-On Reinforcement Learning Course, Part 1 - Dec 22, 2021.
  
  Start your learning journey in Reinforcement Learning with this first of two part tutorial that covers the foundations of the technique with examples and Python code.

  Agents, Beginners, Python, Reinforcement Learning

• An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab - Sep 14, 2021.
  
  Get an Introduction to Reinforcement Learning by attempting to balance a virtual CartPole with OpenAI Gym, RLlib, and Google Colab.

  Google Colab, OpenAI, Python, Reinforcement Learning

• Facebook Launches One of the Toughest Reinforcement Learning Challenges in History - Jun 15, 2021.
  
  The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.

  Challenge, Facebook, Reinforcement Learning

• Getting Started with Reinforcement Learning - Apr 26, 2021.
  
  Demystifying some of the main concepts and terminologies associated with Reinforcement Learning and their association with other fields of AI.

  AI, Beginners, Reinforcement Learning

• DeepMind’s MuZero is One of the Most Important Deep Learning Systems Ever Created - Jan 4, 2021.
  
  MuZero takes a unique approach to solve the problem of planning in deep learning models.

  AlphaZero, Deep Learning, DeepMind, MuZero, Reinforcement Learning

• Facebook Open Sources ReBeL, a New Reinforcement Learning Agent - Dec 14, 2020.
  
  The new model tries to recreate the reinforcement learning and search methods used by AlphaZero in imperfect information scenarios.

  Agents, AI, Facebook, Open Source, Reinforcement Learning

• How to Acquire the Most Wanted Data Science Skills - Nov 13, 2020.
  
  We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.

  Algorithms, Amazon, Apache Spark, AWS, Computer Vision, Data Science, Data Science Skills, Deep Learning, Docker, NLP, NoSQL, PyTorch, Reinforcement Learning, TensorFlow

• How to Make Sense of the Reinforcement Learning Agents? - Oct 30, 2020.
  
  In this blog post, you’ll learn what to keep track of to inspect/debug your agent learning trajectory. I’ll assume you are already familiar with the Reinforcement Learning (RL) agent-environment setting and you’ve heard about at least some of the most common RL algorithms and environments.

  Agents, Deep Learning, Reinforcement Learning

• Deep Learning’s Most Important Ideas - Sep 14, 2020.
  
  In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.

  Attention, Deep Learning, GANs, History, ImageNet, Reinforcement Learning, Transformer

• Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills - Sep 8, 2020.
  
  We analyze the results of the Data Science Skills poll, including 8 categories of skills, 13 core skills that over 50% of respondents have, the emerging/hot skills that data scientists want to learn, and what is the top skill that Data Scientists want to learn.

  Communication, Data Preparation, Data Science Skills, Data Visualization, Excel, GitHub, Mathematics, Poll, Python, Reinforcement Learning, scikit-learn, SQL, Statistics

• The Bitter Lesson of Machine Learning - Jul 15, 2020.
  
  Since that renowned conference at Dartmouth College in 1956, AI research has experienced many crests and troughs of progress through the years. From the many lessons learned during this time, some have needed to be re-learned -- repeatedly -- and the most important of which has also been the most difficult to accept by many researchers.

  AI, AlphaGo, Chess, Machine Learning, Reinforcement Learning, Richard Sutton, Scalability, Trends

• Deepmind’s Gaming Streak: The Rise of AI Dominance - May 27, 2020.
  
  There is still a long way to go before machine agents match overall human gaming prowess, but Deepmind’s gaming research focus has shown a clear progression of substantial progress.

  AI, AlphaGo, Deep Learning, DeepMind, Games, Reinforcement Learning

• DeepMind’s Suggestions for Learning #AtHomeWithAI - May 13, 2020.
  
  DeepMind has been sharing resources for learning AI at home on their Twitter account. Check out a few of these suggestions here, and keep your eye on the #AtHomeWithAI hashtag for more.

  AI, Courses, Deep Learning, DeepMind, Neural Networks, Reinforcement Learning

• What You Need to Know About Deep Reinforcement Learning - May 12, 2020.
  
  How does deep learning solve the challenges of scale and complexity in reinforcement learning? Learn how combining these approaches will make more progress toward the notion of Artificial General Intelligence.

  Deep Learning, Reinforcement Learning

• DeepMind Unveils Agent57, the First AI Agents that Outperforms Human Benchmarks in 57 Atari Games - Apr 13, 2020.
  
  The new reinforcement learning agent innovates over previous architectures achieving one of the most important milestones in the AI space.

  Agents, AI, Atari, DeepMind, Reinforcement Learning

• 2 Things You Need to Know about Reinforcement Learning – Computational Efficiency and Sample Efficiency - Apr 7, 2020.
  
  Experimenting with different strategies for a reinforcement learning model is crucial to discovering the best approach for your application. However, where you land can have significant impact on your system's energy consumption that could cause you to think again about the efficiency of your computations.

  Efficiency, Machine Learning, Reinforcement Learning

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
  
  We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.

  AI, Data Science, Explainability, Geospatial, GPT-2, Key Terms, Machine Learning, Natural Language Generation, Reinforcement Learning, Transformer

• We Created a Lazy AI - Jan 20, 2020.
  
  This article is an overview of how to design and implement reinforcement learning for the real world.

  AI, Reinforcement Learning

• DeepMind Unveils MuZero, a New Agent that Mastered Chess, Shogi, Atari and Go Without Knowing the Rules - Dec 9, 2019.
  
  The new model showed great improvements over the previous AlphaZero agent.

  Agents, AlphaGo, Atari, Chess, DeepMind, Reinforcement Learning, Video Games

• The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II - Nov 18, 2019.
  
  The new AlphaStar achieved Grandmaster level at StarCraft II overcoming some of the limitations of the previous version. How did it do it?

  DeepMind, Reinforcement Learning

• Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal - Nov 11, 2019.
  
  ReAgent is a new framework that streamlines the implementation of reasoning systems.

  Facebook, Reinforcement Learning

• Three Things to Know About Reinforcement Learning - Oct 14, 2019.
  
  As an engineer, scientist, or researcher, you may want to take advantage of this new and growing technology, but where do you start? The best place to begin is to understand what the concept is, how to implement it, and whether it’s the right approach for a given problem.

  MathWorks, Reinforcement Learning

• OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned - Oct 7, 2019.
  
  OpenAI trained agents in a simple game of hide-and-seek and learned many other different skills in the process.

  AI, OpenAI, Reinforcement Learning

• DeepMind Has Quietly Open Sourced Three New Impressive Reinforcement Learning Frameworks - Sep 30, 2019.
  
  Three new releases that will help researchers streamline the implementation of reinforcement learning programs.

  DeepMind, Reinforcement Learning

• Collaborative Evolutionary Reinforcement Learning - Jul 8, 2019.
  
  Intel Researchers created a new approach to RL via Collaborative Evolutionary Reinforcement Learning (CERL) that combines policy gradient and evolution methods to optimize, exploit, and explore challenges.

  Evolutionary Algorithm, Intel, Reinforcement Learning

• How Google uses Reinforcement Learning to Train AI Agents in the Most Popular Sport in the World - Jun 21, 2019.
  
  Researchers from the Google Brain team open sourced Google Research Football, a new environment that leverages reinforcement learning to teach AI agents how to master the most popular sport in the world.

  Agents, AI, Football, Google, Reinforcement Learning, Soccer

• The Emergence of Cooperative and Competitive AI Agents - Jun 19, 2019.
  
  Without specific training in collaboration or competition, a recent AI model from DeepMind uses reinforcement learning to evolve these behaviors in game-playing agents. Learn how this emergent collective intelligence outperforms their human counterparts in 3D multiplayer games.

  Agents, AI, DeepMind, Reinforcement Learning

• Another 10 Free Must-See Courses for Machine Learning and Data Science - Apr 5, 2019.
  
  Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.

  AI, Data Science, Deep Learning, Keras, Machine Learning, NLP, Reinforcement Learning, TensorFlow, U. of Washington, UC Berkeley, Unsupervised Learning

• My favorite mind-blowing Machine Learning/AI breakthroughs - Mar 14, 2019.
  
  We present some of our favorite breakthroughs in Machine Learning and AI in recent times, complete with papers, video links and brief summaries for each.

  AI, AlphaStar, GANs, Generative Adversarial Network, Machine Learning, Machine Translation, Reinforcement Learning, Robots

• 3 Reasons Why AutoML Won’t Replace Data Scientists Yet - Mar 6, 2019.
  
  We dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve.

  Automated Machine Learning, Automation, AutoML, Data Scientist, Feature Engineering, Reinforcement Learning

• Top 10 Technology Trends of 2019 - Feb 7, 2019.
  
  This article outlines 10 top trending technologies for 2019, a list which covers diverse topics such as security, IoT, reinforcement learning, energy sustainability, smart cities, and much more.

  2019 Predictions, Automation, Cloud, Energy, IoT, Reinforcement Learning, Security, Trends

• The 6 Most Useful Machine Learning Projects of 2018 - Jan 15, 2019.
  
  Let’s take a look at the top 6 most practically useful ML projects over the past year. These projects have published code and datasets that allow individual developers and smaller teams to learn and immediately create value.

  Automated Machine Learning, Facebook, fast.ai, Google, Keras, Machine Learning, Object Detection, Python, Reinforcement Learning, Word Embeddings

• 10 More Must-See Free Courses for Machine Learning and Data Science - Dec 20, 2018.
  
  Have a look at this follow-up collection of free machine learning and data science courses to give you some winter study ideas.

  AI, Algorithms, Big Data, Data Science, Deep Learning, Machine Learning, MIT, NLP, Reinforcement Learning, U. of Washington, UC Berkeley, Yandex

• A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more - Dec 7, 2018.
  
  A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.

  Cheat Sheet, Data Science Education, Deep Learning, Machine Learning, Mathematics, Open Source, Reinforcement Learning, Resources, Statistics

• 10 Free Must-See Courses for Machine Learning and Data Science - Nov 8, 2018.
  
  Check out a collection of free machine learning and data science courses to kick off your winter learning season.

  Data Science, Deep Learning, fast.ai, Google, Linear Algebra, Machine Learning, MIT, NLP, Reinforcement Learning, Stanford, Yandex

• Reinforcement Learning: The Business Use Case, Part 2 - Aug 16, 2018.
  
  In this post, I will explore the implementation of reinforcement learning in trading. The Financial industry has been exploring the applications of Artificial Intelligence and Machine Learning for their use-cases, but the monetary risk has prompted reluctance.

  Business, Finance, Machine Learning, Reinforcement Learning, Use Cases

• Reinforcement Learning: The Business Use Case, Part 1 - Aug 9, 2018.
  
  At base, RL is a complex algorithm for mapping observed entities and measures into some set of actions, while optimizing for a long-term or short-term reward.

  Business, Machine Learning, Reinforcement Learning, Use Cases

• Explaining Reinforcement Learning: Active vs Passive - Jun 26, 2018.
  
  We examine the required elements to solve an RL problem, compare passive and active reinforcement learning, and review common active and passive RL techniques.

  Active Learning, Markov Chains, Reinforcement Learning

• 5 Things You Need to Know about Reinforcement Learning - Mar 28, 2018.
  
  With the popularity of Reinforcement Learning continuing to grow, we take a look at five things you need to know about RL.

  Machine Learning, Markov Chains, Reinforcement Learning, Richard Sutton

• Resurgence of AI During 1983-2010 - Feb 16, 2018.
  
  We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.

  AI, Big Data, History, Machine Learning, Neural Networks, Reinforcement Learning, Trends

• NIPS 2017 Key Points & Summary Notes - Dec 18, 2017.
  
  Third year Ph.D student David Abel, of Brown University, was in attendance at NIP 2017, and he labouriously compiled and formatted a fantastic 43-page set of notes for the rest of us. Get them here.

  Bias, Conference, Machine Learning, NeurIPS, NIPS, Reinforcement Learning

• When reinforcement learning should not be used? - Dec 6, 2017.
  
  While reinforcement learning has achieved many successes, there are situations when it use is problematic. We describe the issues and how to work around them.

  Deep Learning, Online Games, Reinforcement Learning, Self-Driving Car

• Exclusive: Interview with Rich Sutton, the Father of Reinforcement Learning - Dec 5, 2017.
  
  My exclusive interview with Rich Sutton, the Father of Reinforcement Learning, on RL, Machine Learning, Neuroscience, 2nd edition of his book, Deep Learning, Prediction Learning, AlphaGo, Artificial General Intelligence, and more.

  AGI, AI, AlphaGo, DeepMind, Machine Learning, Neuroscience, Reinforcement Learning, Richard Sutton, Yann LeCun

• Machine Learning Algorithms: Which One to Choose for Your Problem - Nov 14, 2017.
  
  This article will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks. At the end of the article, you’ll find the structured overview of the main features of described algorithms.

  Algorithms, Machine Learning, Reinforcement Learning, Statsbot, Supervised Learning, Unsupervised Learning

• 3 different types of machine learning - Nov 1, 2017.
  
  In this extract from “Python Machine Learning” a top data scientist Sebastian Raschka explains 3 main types of machine learning: Supervised, Unsupervised and Reinforcement Learning. Use code PML250KDN to save 50% off the book cost.

  Pages: 1 2

  Classification, Clustering, Machine Learning, Regression, Reinforcement Learning, Supervised Learning

• AlphaGo Zero: The Most Significant Research Advance in AI - Oct 27, 2017.
  
  The previous version of AlphaGo beat the human world champion in 2016. The new AlphaGo Zero beat the previous version by 100 games to 0, and learned Go completely on its own. We examine what this means for AI.

  AI, AlphaGo, DeepMind, Google, Reinforcement Learning, Xavier Amatriain

• 5 Ways to Get Started with Reinforcement Learning - Sep 20, 2017.
  
  We give an accessible overview of reinforcement learning, including Deep Q Learning, and provide useful links for implementing RL.

  Deep Learning, Machine Learning, Neural Networks, Reinforcement Learning

• Which Machine Learning Algorithm Should I Use? - Jun 1, 2017.
  
  A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is "which algorithm should I use?” The answer to the question varies depending on many factors, including the size, quality, and nature of data, the available computational time, and more.

  Algorithms, Cheat Sheet, Machine Learning, Reinforcement Learning, Supervised Learning, Unsupervised Learning

• 5 Machine Learning Projects You Can No Longer Overlook, May - May 10, 2017.
  
  In this month's installment of Machine Learning Projects You Can No Longer Overlook, we find some data preparation and exploration tools, a (the?) reinforcement learning "framework," a new automated machine learning library, and yet another distributed deep learning library.

  Automated Machine Learning, Data Exploration, Deep Learning, Distributed Systems, Machine Learning, Overlook, Pandas, Reinforcement Learning

• Greed, Fear, Game Theory and Deep Learning - Mar 3, 2017.
  
  The most advanced kind of Deep Learning system will involve multiple neural networks that either cooperate or compete to solve problems. The core problem of a multi-agent approach is how to control its behavior.

  AI, Deep Learning, Reinforcement Learning

• 5 Free Courses for Getting Started in Artificial Intelligence - Feb 1, 2017.
  
  A carefully-curated list of 5 free collections of university course material to help you better understand the various aspects of what artificial intelligence and skills necessary for moving forward in the field.

  AI, Artificial Intelligence, Deep Learning, MIT, Reinforcement Learning, Self-Driving Car, UC Berkeley

• 6 areas of AI and Machine Learning to watch closely - Jan 25, 2017.
  
  Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.

  AI, Deep Neural Network, Generative Adversarial Network, Machine Learning, Reinforcement Learning

• Eat Melon: A Deep Q Reinforcement Learning Demo in your browser - Jan 20, 2017.
  
  Check "Eat Melon demo", a fun way to gain familiarity with the Deep Q Learning algorithm, which you can do in your browser.

  Atari, Deep Learning, OpenAI, Reinforcement Learning

• Deep Learning Research Review: Reinforcement Learning - Nov 25, 2016.
  
  This edition of Deep Learning Research Review explains recent research papers in Reinforcement Learning (RL). If you don't have the time to read the top papers yourself, or need an overview of RL in general, this post has you covered.

  Pages: 1 2

  Deep Learning, Machine Learning, Reinforcement Learning

• 5 EBooks to Read Before Getting into A Machine Learning Career - Oct 21, 2016.
  
  A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.

  Bayesian, Data Science, Deep Learning, Free ebook, Machine Learning, Reinforcement Learning

• Reinforcement Learning and the Internet of Things - Aug 5, 2016.
  
  Gain an understanding of how reinforcement learning can be employed in the Internet of Things world.

  Brandon Rohrer, Internet of Things, IoT, Reinforcement Learning, Richard Sutton

• The Hard Problems AI Can’t (Yet) Touch - Jul 11, 2016.
  
  It's tempting to consider the progress of AI as though it were a single monolithic entity, advancing towards human intelligence on all fronts. But today's machine learning only addresses problems with simple, easily quantified objectives

  AI, Machine Learning, Optimization, Reinforcement Learning, Supervised Learning

• Are Deep Neural Networks Creative? - May 12, 2016.
  
  Deep neural networks routinely generate images and synthesize text. But does this amount to creativity? Can we reasonably claim that deep learning produces art?

  Artificial Intelligence, Deep Learning, Generative Adversarial Network, Generative Models, Recurrent Neural Networks, Reinforcement Learning, Zachary Lipton