Search results for Reinforcement Learning

    Found 100 documents, 10397 searched:

  • Exclusive: Interview with Rich Sutton, the Father of Reinforcement Learning

    ...which is interpreted into a reward and a representation of the state, which are fed back into the agent. Source: Wikipedia Rich Sutton: Reinforcement learning is learning from rewards, by trial and error, during normal interaction with the world. This makes it very much like natural learning...

    https://www.kdnuggets.com/2017/12/interview-rich-sutton-reinforcement-learning.html

  • Three Things to Know About Reinforcement Learning

    ...nd what the concept is, how to implement it, and whether it’s the right approach for a given problem . If we simplify the concept, at its foundation, reinforcement learning is a type of machine learning that has the potential to solve toughdecision-making problems. But to truly understand how it...

    https://www.kdnuggets.com/2019/10/mathworks-reinforcement-learning.html

  • Deep Learning Research Review: Reinforcement Learning

    ...st talk about what reinforcement learning is. The field of machine learning can be separated into 3 main categories. Supervised Learning Unsupervised Learning Reinforcement Learning The first category, supervised learning, is the one you may be most familiar with. It relies on the idea of creating...

    https://www.kdnuggets.com/2016/11/deep-learning-research-review-reinforcement-learning.html

  • Is “Artificial Intelligence” Dead? Long Live Deep Learning?!?

    ...portrayed as a big success for deep learning, but it's actually a combination of ideas from several different areas of AI and machine learning: deep learning, reinforcement learning, self-play, Monte Carlo tree search, etc. A future master algorithm will be sufficient for AI, by definition,...

    https://www.kdnuggets.com/2016/08/artificial-intelligence-dead-long-live-deep-learning.html

  • Getting Started with Machine Learning in One Hour!

    ...ual size. With these patterns, records/data is clustered into groups like Luxury-Homes, Non-Luxury Homes, Bunglows, Apartment, etc. Reinforcement: In Reinforcement Learning, an ‘Agent’ acts in an ‘Environment’ and receives positive or negative feedback. Positive feedback tells an agent that it has...

    https://www.kdnuggets.com/2017/11/getting-started-machine-learning-one-hour.html

  • 5 Things You Need to Know about Reinforcement Learning

    ...for performing a task, reinforcement learning uses rewards and punishment as signals for positive and negative behavior. As compared to unsupervised learning, reinforcement learning is different in terms of goals. While the goal in unsupervised learning is to find similarities and differences...

    https://www.kdnuggets.com/2018/03/5-things-reinforcement-learning.html

  • Reinforcement Learning and the Internet of Things

    ...we begin, here is a brief introduction of Reinforcement learning. This section is adapted from a book by Richard Sutton (MIT Press) on reinforcement learning. Reinforcement learning is learning what to do i.e. how to map situations to actions--so as to maximize a numerical reward signal. Unlike...

    https://www.kdnuggets.com/2016/08/reinforcement-learning-internet-things.html

  • 5 Ways to Get Started with Reinforcement Learning

    …l´ denotes next. e.g. s´ denotes next state. Figure 1.0 Deep Q Learning training framework. Credit: Robert Aguilera Extending Reinforcement Learning Reinforcement learning works well with many things (such as AlphaGo), but it often fails in places where the feedback is sparse. The agent…

    https://www.kdnuggets.com/2017/09/5-ways-get-started-reinforcement-learning.html

  • 3 different types of machine learning

    …learned from this data to predict the outcome variable of new data: Solving interactive problems with reinforcement learning Another type of machine learning is reinforcement learning. In reinforcement learning, the goal is to develop a system (agent) that improves its performance based on…

    https://www.kdnuggets.com/2017/11/3-different-types-machine-learning.html

  • How AI will transform healthcare (and can it fix the US healthcare system?)">Silver BlogHow AI will transform healthcare (and can it fix the US healthcare system?)

    ...ill see remote surgery with 5G become a norm: Robots designed to assist with the care of the elderly (and in time trained with Deep Learning and Deep Reinforcement Learning): Robots trained with AI interacting with humans. Robot passes medical exams in China: The problem facing healthcare...

    https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

  • Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018">Gold BlogMachine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018

    ...ight of the year, that has to go to AlphaGo Zero (paper). Not only does this new approach improve in some of the most promising directions (e.g. deep reinforcement learning), but it also represents a paradigm shift in which such models can learn without data. We have also learned very recently that...

    https://www.kdnuggets.com/2017/12/machine-learning-ai-main-developments-2017-key-trends-2018.html

  • AI, Data Science, Machine Learning: Main Developments in 2016, Key Trends in 2017

    ...reatly improved the conference for all participants. Nikita Johnson, Founder, RE•WORK 1. At RE•WORK events over the course of 2016, both unsupervised learning and reinforcement learning became a more prominent feature in talks and discussions, startups taking part to the industry leaders in the...

    https://www.kdnuggets.com/2017/01/ai-data-science-machine-learning-key-trends.html

  • 5 EBooks to Read Before Getting into A Machine Learning Career">Gold Blog5 EBooks to Read Before Getting into A Machine Learning Career

    ...ast few decades, which authors often want to cover tangentially even in introductory texts. There is, however, a lot of information about statistical learning, learning theory, classification, and a variety of algorithms to whet your appetite. At < 200 pages, this can be read rather quickly. 2....

    https://www.kdnuggets.com/2016/10/5-free-ebooks-machine-learning-career.html

  • Transforming from Autonomous to Smart: Reinforcement Learning Basics

    ...te. So we are going to use this blog to deep dive into the category of artificial intelligence called reinforcement learning. We are going to see how reinforcement learning might help us to address these challenges; to work smarter at the edge when brute force technology advances will not suffice....

    https://www.kdnuggets.com/2017/08/transforming-autonomous-smart-reinforcement-learning-basics.html

  • Introduction to Active Learning

    ...nd active learning can reduce the number of required labels for your models, they are very different concepts. On the one hand, we have reinforcement learning. Reinforcement learning is a goal-oriented learning approach inspired by behavioral psychology that allows you to take inputs from the...

    https://www.kdnuggets.com/2018/10/introduction-active-learning.html

  • Another 10 Free Must-See Courses for Machine Learning and Data Science">Platinum BlogAnother 10 Free Must-See Courses for Machine Learning and Data Science

    ...ultiple machines. The goal of the course is to provide both a good understanding and good ability to build modern nonparametric estimators.   7. Reinforcement Learning University of Waterloo The course introduces students to the design of algorithms that enable machines to learn based on...

    https://www.kdnuggets.com/2019/04/another-10-free-must-see-courses-machine-learning-data-science.html

  • Machine Learning & AI Main Developments in 2018 and Key Trends for 2019">Gold BlogMachine Learning & AI Main Developments in 2018 and Key Trends for 2019

    ...re something like: I saw a video of that guy saying those words. We stopped believing printed words decades ago, but video was unshakeable until now. Reinforcement learning comeback in the form of deep learning was quite unexpected and cool! Google's system that calls restaurants on your behalf and...

    https://www.kdnuggets.com/2018/12/predictions-machine-learning-ai-2019.html

  • How Google uses Reinforcement Learning to Train AI Agents in the Most Popular Sport in the World

    ...football environments. But what if AI agents could learn to play football by simply playing? That was the strategy followed by the Google Brain team. Reinforcement Learning for Football   The idea of applying reinforcement learning to football environments seems intuitive. After all,...

    https://www.kdnuggets.com/2019/06/google-reinforcement-learning-ai-agents-sport.html

  • A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more

    ...ning Book This textbook by Ian Goodfellow, Yoshua Bengio, and Aaron Courville is probably the closest we have to a de-facto standard textbook for DL. Reinforcement Learning File Description Sutton and Barto Open RL Book De-facto standard intro to RL, even though the textbook is only now about to be...

    https://www.kdnuggets.com/2018/12/finlayson-machine-learning-resources.html

  • Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017">Gold BlogMachine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017

    ...lligence/Machine Learning related events in 2016 and what key trends do you see in 2017?" Common themes include the triumphs of deep neural networks, reinforcement learning's successes, AlphaGo as exemplar of the power of both of these phenomena in unison, the application of machine learning to the...

    https://www.kdnuggets.com/2016/12/machine-learning-artificial-intelligence-main-developments-2016-key-trends-2017.html

  • Reinforcement Learning: The Business Use Case, Part 2

    ...y Aishwarya Srinivasan, Deep Learning Researcher In my previous post, I focused on the understanding of computational and mathematical perspective of reinforcement learning, and the challenges we face when using the algorithm on business use cases. In this post, I will explore the implementation of...

    https://www.kdnuggets.com/2018/08/reinforcement-learning-business-use-case-part-2.html

  • Machine Learning Meets Humans – Insights from HUML 2016

    …tions in critical domains, ostensibly the purpose of the talk. He cited adversarial examples as one problem, motivating startup.ML’s growing focus on reinforcement learning. This struck me as odd. There is no good reason to suspect that reinforcement learning is safer than supervised learning in…

    https://www.kdnuggets.com/2017/01/machine-learning-humans-huml-2016.html

  • Resurgence of AI During 1983-2010

    ...ning sub-groups, which may contain sub-sub groups and so on. K-means clustering is often used for creating hierarchical groups as well. Reinforcement Learning Reinforcement Learning (RL) algorithms learn from the consequences of their actions, rather than from being taught by humans or by using...

    https://www.kdnuggets.com/2018/02/resurgence-ai-1983-2010.html

  • The Deception of Supervised Learning

    ...y, can be addressed within the supervised learning paradigm. Others, like causality, might require us to pursue fundamentally more powerful models of learning. Reinforcement learning (RL), for example, directly models an agent acting within a sequential decision making process. The framework...

    https://www.kdnuggets.com/2016/09/deception-of-supervised-learning.html

  • What To Expect from Deep Learning in 2016 and Beyond

    …. Koray Kavukcuoglu & Alex Graves, Research Scientists at Google DeepMind : A lot will happen in the next five years. We expect both unsupervised learning and reinforcement learning to become more prominent. We also expect an increase in multimodal learning, and a stronger focus on learning

    https://www.kdnuggets.com/2016/01/deep-learning-2016-beyond.html

  • Reinforcement Learning: The Business Use Case, Part 1

    comments By Aishwarya Srinivasan, Deep Learning Researcher The whirl of reinforcement learning started with the advent of AlphaGo by DeepMind, the AI system built to play the game Go. Since then, various companies have invested a great deal of time, energy, and research, and today reinforcement...

    https://www.kdnuggets.com/2018/08/reinforcement-learning-business-use-case-part-1.html

  • AI Conference in San Francisco, Sep 2017 – highlights and key ideas

    ...lications are probably internet advertising or deciding loan applications. Four promising areas: Supervised learning, Transfer learning, Unsupervised learning, Reinforcement learning. A specific word of advice for learners: go through research papers and try to replicate the findings. Backing off...

    https://www.kdnuggets.com/2017/09/jsmudhol-ai-conference-san-francisco-highlights.html

  • What are Some “Advanced” AI and Machine Learning Online Courses?

    ...before but since moved to Prof. Mostafa’s home page. The link point there. It is a great foundational course in deep mathematical aspects of machine learning and learning theory in general. “Machine Learning Fundamentals” by UC San Diego on edX: A well-balanced course teaching core theoretical and...

    https://www.kdnuggets.com/2019/02/some-advanced-ai-machine-learning-online-courses.html

  • Data Science Predicting The Future

    ...ith unsupervised learning labelling the data, and supervised learning finding the best model to fit the data. One instance of this is semi-supervised learning. Reinforcement learning This is a type of machine learning where the focus is on performance (to walk, to see, to read), instead of...

    https://www.kdnuggets.com/2018/06/data-science-predicting-future.html

  • Which Machine Learning Algorithm Should I Use?">Gold Blog, May 2017Which Machine Learning Algorithm Should I Use?

    ...l features and some features are redundant or irrelevant to the task. Reducing the dimensionality helps to find the true, latent relationship.   Reinforcement learning Reinforcement learning analyzes and optimizes the behavior of an agent based on the feedback from the environment....

    https://www.kdnuggets.com/2017/06/which-machine-learning-algorithm.html

  • 10 Free Must-See Courses for Machine Learning and Data Science">Gold Blog10 Free Must-See Courses for Machine Learning and Data Science

    ...); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data...

    https://www.kdnuggets.com/2018/11/10-free-must-see-courses-machine-learning-data-science.html

  • Explaining Reinforcement Learning: Active vs Passive

    ...times we want an agent to be forced to pick an action in every state. The exploration function converts a passive agent into an active one.   Q-Learning Q-learning is a TD learning method which does not require the agent to learn the transitional model, instead learns Q-value functions Q(s,...

    https://www.kdnuggets.com/2018/06/explaining-reinforcement-learning-active-passive.html

  • Machine Learning Algorithms: Which One to Choose for Your Problem">Silver BlogMachine Learning Algorithms: Which One to Choose for Your Problem

    ...scribed algorithms. First of all, you should distinguish 4 types of Machine Learning tasks: Supervised learning Unsupervised learning Semi-supervised learning Reinforcement learning Supervised learning Supervised learning is the task of inferring a function from labeled training data. By fitting to...

    https://www.kdnuggets.com/2017/11/machine-learning-algorithms-choose-your-problem.html

  • 6 areas of AI and Machine Learning to watch closely">Gold Blog6 areas of AI and Machine Learning to watch closely

    …i (Oxford) Original post. Reposted with permission. Bio: Nathan Benaich Invests in tech companies @PlayfairCapital. All things data, machine intelligence, user experiences. Former cancer researcher, photographer, perpetual foodie. Related: Continuous improvement for IoT through AI / Continuous…

    https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html

  • ICLR 2019 highlights: Ian Goodfellow and GANs, Adversarial Examples, Reinforcement Learning, Fairness, Safety, Social Good, and all that jazz

    ...tations, there wasn’t much work on learning representations for structured or tabular data. The notes below are grouped according to the main topics. Reinforcement Learning There were three workshops and an entire poster session (~90 papers) dedicated to Reinforcement Learning. One of the prominent...

    https://www.kdnuggets.com/2019/05/iclr-2019-highlights.html

  • Taxonomy of Methods for Deep Meta Learning

    ...ks selecting weight initialization, learning hyperparameters and layers.   Two recent papers that were submitted to ICLR 2017 explore the use of Reinforcement learning to learn new kinds of Deep Learning architectures (“Designing Neural Network Architectures using Reinforcement Learning” and...

    https://www.kdnuggets.com/2017/06/taxonomy-methods-deep-meta-learning.html

  • Artificial Intelligence and Data Science Advances in 2018 and Trends for 2019

    ...ress in deep learning for computer vision, natural language processing (NLP), and audio signal processing. The expert’s hot topic list includes GANs, reinforcement learning, the use of invertible neural networks (INNs) for generative modeling, as well as connectivity patterns in neural networks...

    https://www.kdnuggets.com/2019/02/ai-data-science-advances-trends.html

  • How to Start Learning Deep Learning

    ...uses much more on theory than the Coursera class but it is still relevant for beginners. Knowledge in machine learning isn’t really a prerequisite to learning deep learning, but it does help. In addition, learning classical machine learning and not only deep learning is important because it...

    https://www.kdnuggets.com/2016/07/start-learning-deep-learning.html

  • Deep Learning in Neural Networks: An Overview

    ...hs and the question of how deep is deep?; Key themes of Deep Learning; Highlights in the development of Supervised and Unsupervised Learning methods, Reinforcement Learning; and a short look at where things might be heading. How deep is deep? We don’t know, but ’10’ is very deep… Which modifiable...

    https://www.kdnuggets.com/2016/04/deep-learning-neural-networks-overview.html

  • Top 20 Deep Learning Papers, 2018 Edition">Gold BlogTop 20 Deep Learning Papers, 2018 Edition

    ...nable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks. 5....

    https://www.kdnuggets.com/2018/03/top-20-deep-learning-papers-2018.html

  • Top arXiv Papers, January: ConvNets Advances, Wide Instead of Deep, Adversarial Networks Win, Learning to Reinforcement Learn

    ...s that combine GANs with other methods. Finally, the tutorial contains three exercises for readers to complete, and the solutions to these exercises. Learning to reinforcement learn   Jane X Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z Leibo, Remi Munos, Charles Blundell,...

    https://www.kdnuggets.com/2017/02/top-arxiv-papers-january-convnets-wide-adversarial.html

  • My favorite mind-blowing Machine Learning/AI breakthroughs">Silver BlogMy favorite mind-blowing Machine Learning/AI breakthroughs

    ...he CEO of NVIDIA, show a video (made with this technique) of himself dancing like Michael Jackson. I’m glad I attended the GPU Tech Conference, haha. Reinforcement learning World models — AI learning inside its own dream Website by Google Brain, 2018 Humans do not actually know or think about all...

    https://www.kdnuggets.com/2019/03/favorite-ml-ai-breakthroughs.html

  • The Hard Problems AI Can’t (Yet) Touch

    ...consider the progress of AI as though it were a single monolithic entity, advancing equally on all fronts. And if we restrict attention to supervised learning and reinforcement learning for games, this seems believable. But we should pause before giving in to Singularitarian magical thinking about...

    https://www.kdnuggets.com/2016/07/hard-problems-ai-cant-yet-touch.html

  • The 10 Algorithms Machine Learning Engineers Need to Know">2016 Gold BlogThe 10 Algorithms Machine Learning Engineers Need to Know

    ...ing algorithms that I learned from the course. Machine learning algorithms can be divided into 3 broad categories — supervised learning, unsupervised learning, and reinforcement learning.Supervised learning is useful in cases where a property (label) is available for a certain dataset (training...

    https://www.kdnuggets.com/2016/08/10-algorithms-machine-learning-engineers.html

  • The Next Challenges for Reinforcement Learning

    ..., and DeepMind has open-sourced their own in-house developed 3D environment. These 3D environments focus RL research on challenges such as multi-task learning, learning to remember and safe and effective exploration. Below, we discuss these challenges in more detail. Multi-Task Learning   To...

    https://www.kdnuggets.com/2017/03/next-challenges-reinforcement-learning.html

  • The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II

    ...illustrating the trajectory from the first version of AlphaStar to the current one as well as some of the key challenges of StarCraft II. The use of reinforcement learning to master multi-player games is certainly nothing novel. In recent months, AI agents such as OpenAI Five and DeepMind’s FTW...

    https://www.kdnuggets.com/2019/11/reinforcement-learning-methods-alphastar-outcompete-human-players-starcraft.html

  • Another 10 Free Must-Read Books for Machine Learning and Data Science">Platinum BlogAnother 10 Free Must-Read Books for Machine Learning and Data Science

    ...ure engineering and model interpretability, an intro to deep learning, a book on Python programming, a pair of data visualizations entrants, and twin reinforcement learning efforts. There's nothing left to say but "get reading!"   1. Mathematics for Machine Learning By Marc Peter Deisenroth,...

    https://www.kdnuggets.com/2019/03/another-10-free-must-read-books-for-machine-learning-and-data-science.html

  • Deep Learning for NLP: An Overview of Recent Trends">Silver BlogDeep Learning for NLP: An Overview of Recent Trends

    ...Some topics include: The rise of distributed representations (e.g., word2vec) Convolutional, recurrent, and recursive neural networks Applications in reinforcement learning Recent development in unsupervised sentence representation learning Combining deep learning models with memory-augmenting...

    https://www.kdnuggets.com/2018/09/deep-learning-nlp-overview-recent-trends.html

  • Collaborative Evolutionary Reinforcement Learning

    comments By Somdeb Majumdar, Deep Learning Data Scientist, Intel AI Lab. An important, emerging branch of machine learning is reinforcement learning (RL). In RL, the machine learns which action to take in order to maximize its reward; it can be a physical action, like a robot moving an arm, or a...

    https://www.kdnuggets.com/2019/07/collaborative-evolutionary-reinforcement-learning.html

  • 5 Machine Learning Projects You Can No Longer Overlook, May

    ...g for some quick and dirty summarization. 2. Gym You've heard of OpenAI's Gym... but what is it? OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This is the gym open-source library, which gives you access to an ever-growing variety of environments. If you're...

    https://www.kdnuggets.com/2017/05/five-machine-learning-projects-cant-overlook-may.html

  • Best (and Free!!) Resources to Understand Nuts and Bolts of Deep Learning

    ...n are reviewed here. There is also a very common question about whether to use convnets or RNNs (LSTMs/GRUs) on text. A good overview is here.   Reinforcement Learning   Sutton and Barto is the bible to get started with these methods. The book is free and is available here. A very good...

    https://www.kdnuggets.com/2018/07/best-free-resources-understand-nuts-bolts-deep-learning.html

  • What should be focus areas for Machine Learning / AI in 2018?

    ...nsical) images which generate high confidence misclassifications. However, as shown by the Goolge Deep Mind team who used deep learning combined with reinforcement learning for the Atari game playing system or the AlphaGo, the Go game playing system which combined deep learning with MonteCarlo tree...

    https://www.kdnuggets.com/2018/04/focus-areas-ml-ai-2018.html

  • DeepMind Has Quietly Open Sourced Three New Impressive Reinforcement Learning Frameworks

    ...u can imagine, gaming environments are far from trivial to assemble. OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. The purpose of OpenSpiel is to promote general multiagent reinforcement learning across many...

    https://www.kdnuggets.com/2019/09/deepmind-three-new-impressive-reinforcement-learning-frameworks.html

  • When reinforcement learning should not be used?

    comments By Jason Xie. I'll discuss some of the issues reinforcement learning faces. Reinforcement learning describes the set of learning problems where an agent must take actions in an environment in order to maximize some defined reward function. Unlike supervised deep learning, large amounts...

    https://www.kdnuggets.com/2017/12/when-reinforcement-learning-not-used.html

  • Greed, Fear, Game Theory and Deep Learning

    ...eepMind presents their latest research on this subject titled “Understanding Agent Cooperation”. The gist of the research is that, they employed Deep Reinforcement Learning networks in two game environments to study their behavior. The motivation is to study multi-agent systems to better understand...

    https://www.kdnuggets.com/2017/03/greed-fear-game-theory-deep-learning.html

  • Awesome Deep Learning: Most Cited Deep Learning Papers">Gold Blog, Apr 2017Awesome Deep Learning: Most Cited Deep Learning Papers

    ...learning techniques for learning human / robot motions. Original. Reposted with permission. Related: Top 20 Recent Research Papers on Machine Learning and Deep Learning Top arXiv Papers, January: ConvNets Advances, Wide Instead of Deep, Adversarial Networks Win, Learning to Reinforcement Learn Top...

    https://www.kdnuggets.com/2017/04/awesome-deep-learning-most-cited-papers.html

  • Evolving Deep Neural Networks

    ...int the search space but is susceptible to get trapped by local optima, saddle points and noisy gradients, especially in dense solution areas such as reinforcement learning [6]. Illustration of a function with noisy gradients and several local minima. A gradient following algorithm such as SGD will...

    https://www.kdnuggets.com/2019/06/evolving-deep-neural-networks.html

  • ODSC India Highlights: Deep Learning Revolution in Speech, AI Engineer vs Data Scientist, and Reinforcement Learning for Enterprise

    ...e sessions running in parallel and one could choose to attend any of them based on their interests. Below is a summary of few interesting sessions on Reinforcement learning, Sarcasm Detection and Conversational Agents . Samiran Roy , Data Scientist at Envestnet Yodlee conducted a session on...

    https://www.kdnuggets.com/2018/09/odsc-india-highlights.html

  • Machine Learning Key Terms, Explained

    ...rning is a process, like data mining, which employs deep neural network architectures, which are particular types of machine learning algorithms. 10. Reinforcement Learning   Bishop best describes reinforcement learning in a single concise sentence: "Reinforcement learning is concerned with...

    https://www.kdnuggets.com/2016/05/machine-learning-key-terms-explained.html

  • Game Theory Reveals the Future of Deep Learning">Gold BlogGame Theory Reveals the Future of Deep Learning

    ...Deep Learning I would really love to see an entire text book written with this approach! David Silver and Johannes Heinrich have a paper titled “Deep Reinforcement Learning from Self-Play in Imperfect-Information Games”. They write: We have introduced NFSP, the first end-to-end deep reinforcement...

    https://www.kdnuggets.com/2016/12/game-theory-reveals-future-deep-learning.html

  • An Introduction to Semi-supervised Reinforcement Learning

    ...from the unlabelled episodes. I think that semi-supervised RL is a valuable ingredient for AI control, as well as an interesting research problem in reinforcement learning. Applications and motivation   Application to AI control: expensive reward functions As a simple example, consider an RL...

    https://www.kdnuggets.com/2016/05/intro-semi-supervised-reinforcement-learning.html

  • 3 Reasons Why AutoML Won’t Replace Data Scientists Yet

    ...gent receives a reward. Otherwise, it is punished. This way, the agent learns from its mistakes and improves with experience. Similarly to supervised learning, in reinforcement learning, there is a measure of success, which makes this ML task amenable to automation. However, to the best of our...

    https://www.kdnuggets.com/2019/03/why-automl-wont-replace-data-scientists.html

  • 5 Things You Need To Know About Data Science

    I am frequently asked questions about Data Science, so here my answers to some frequent questions and 5 useful things to know about Data Science and Data Scientists. 1. Business Intelligence, Business Analytics, Data Science, Data Analytics, Data Mining, Predictive Analytics - what are the...

    https://www.kdnuggets.com/2018/02/5-things-about-data-science.html

  • Top 10 Machine Learning Algorithms for Beginners">Platinum BlogTop 10 Machine Learning Algorithms for Beginners

    ...m is a Feature Extraction approach. Algorithms 6-8 that we cover here - Apriori, K-means, PCA are examples of unsupervised learning. 3. Reinforcement learning: Reinforcement learning is a type of machine learning algorithm that allows the agent to decide the best next action based on its current...

    https://www.kdnuggets.com/2017/10/top-10-machine-learning-algorithms-beginners.html

  • Scikit-Learn & More for Synthetic Dataset Generation for Machine Learning

    ...es sound made by musical instruments of various kinds. Here is the detailed description of the dataset. The NSynth dataset Synthetic environments for reinforcement learning OpenAI Gym The greatest repository for synthetic learning environment for reinforcement ML is OpenAI Gym. It consists of a...

    https://www.kdnuggets.com/2019/09/scikit-learn-synthetic-dataset.html

  • Eat Melon: A Deep Q Reinforcement Learning Demo in your browser

    ...llar/UIC. The Eat Melon demo is a fun way to gain familiarity with the Deep Q Learning algorithm. The Deep Q learning algorithm falls in the class of reinforcement learning algorithms. In reinforcement learning, an agent learns by trying to maximize a cumulative reward. In this way, the agent...

    https://www.kdnuggets.com/2017/01/eat-melon-deep-q-reinforcement-learning-demo.html

  • Data Science in 30 minutes, Artificial General Intelligence, and Answers to your Questions

    ...erhuman abilities in 3 games: Go, Chess, and Shogi. AlphaZero started with no chess knowledge (hence the name) - just rules of the game. It used Deep Learning, Reinforcement Learning, and massive compute power. It played itself and after 4 hours and a few million games, it reached a superhuman...

    https://www.kdnuggets.com/2018/01/piatetsky-data-science-30-minutes-agi.html

  • The Machine Learning Algorithms Used in Self-Driving Cars">Gold Blog, May 2017The Machine Learning Algorithms Used in Self-Driving Cars

    …rvised and supervised learning. For each training example, there is a target label in supervised learning; there are no labels at all in unsupervised learning; the reinforcement learning consists of time-delayed and sparse labels – the future rewards. The agent learns to behave in environment…

    https://www.kdnuggets.com/2017/06/machine-learning-algorithms-used-self-driving-cars.html

  • 5 Free Courses for Getting Started in Artificial Intelligence

    ...e) Contact information While mentioned that the homework assignments are not public, a series of progressing Pacman projects are, which cover search, reinforcement learning, classification, and beyond. Led by professors Dan Klein and Pieter Abbeel, the lectures, videos, exams, and other materials...

    https://www.kdnuggets.com/2017/02/5-free-courses-getting-started-artificial-intelligence.html

  • Design by Evolution: How to evolve your neural network with AutoML

    ...ally tells us how the whole system has performed. This type of reward is not a differentiable function! Remind you of something? Yes, it is a typical Reinforcement Learningscenario! Quoting wikipedia on RL: Reinforcement learning (RL) is an area of machine learning inspired by behaviourist...

    https://www.kdnuggets.com/2017/07/design-evolution-evolve-neural-network-automl.html

  • Top KDnuggets tweets, Feb 21-27: Top 20 Python #AI and #MachineLearning Open Source Projects; Intro to Reinforcement Learning Algorithms

    ...: Top 20 Python #AI and #MachineLearning Open Source Projects https://t.co/ZVfYZL0wAc https://t.co/tiiyJfE6sf Most Favorited: Introduction to Various Reinforcement Learning Algorithms Part I (Q-Learning, SARSA, DQN, DDPG) https://t.co/NEXygD3zry https://t.co/7qxKyjfplM Most Viewed: Top 20 Python...

    https://www.kdnuggets.com/2018/02/top-tweets-feb21-27.html

  • An Inside Update on Natural Language Processing

    ...there academic computational-linguistics work that you'd call out as interesting, surfaced in NLP software tools or not? Two items: vectorization and reinforcement learning. The vectorization of words and phrases is one of the big overall trends these days, with the use of those vectors as the...

    https://www.kdnuggets.com/2016/06/inside-update-natural-language-processing.html

  • Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal

    ...Horizon streamlines the use of PyTorch for model experimentation and training while Caffe2 is reserved for production workflows. A typically Horizon reinforcement learning workflow includes a Spark pipeline for time generation, followed by a feature extraction and normalization module based on...

    https://www.kdnuggets.com/2019/11/facebook-adds-this-new-framework-reinforcement-learning-arsenal.html

  • Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners

    ...i5 8 GB 1600 MHz DDR3 Intel Iris 1536 MB pic.twitter.com/5I3Vn5HSRg— Sam Putnam (@samdeeplearning) February 15, 2017 3. Flappy Bird using Deep Reinforcement Learning (Deep Q-learning) Model: Demo (Amazon version): Deep reinforcement learning-drone hovers,lrns pkg sizes....

    https://www.kdnuggets.com/2017/06/deep-learning-demos-code-beginners.html

  • An Introduction to AI">Silver BlogAn Introduction to AI

    ...o generalise and perform in unseen scenarios. Methods (non-exhaustive list) Regression, Clustering and Classification are the 3 main areas of Machine Learning. Reinforcement Learning: is an area that deals with modelling agents in an environment that continuously rewards the agent for taking the...

    https://www.kdnuggets.com/2018/11/an-introduction-ai.html

  • Top KDnuggets tweets, Nov 22-28: Reinforcement Learning: An Introduction by Sutton and Barto – Complete Second Draft

    ...g: An Introduction by Sutton & Barto - Complete Second Draft now freely available https://t.co/vCvwtxCOKL https://t.co/ycD5F4Mh7O Most Favorited: Reinforcement Learning: An Introduction by Sutton & Barto - Complete Second Draft now freely available https://t.co/vCvwtxCOKL...

    https://www.kdnuggets.com/2017/11/top-tweets-nov22-28.html

  • KDnuggets™ News 17:n46, Dec 6: Why You Should Forget for-loop for Data Science Code; Reinforcement Learning: Exclusive Interview with Rich Sutton; Big Data Key Trends

    ...Top Stories, Nov 27-Dec 3: Embracing Vectorization in Data Science; Understanding Deep Convolutional Neural Networks Top KDnuggets tweets, Nov 22-28: Reinforcement Learning: An Introduction by Sutton and Barto - Complete Second Draft   News Chatbots Gone Wild DataRobot: Moving from BI to...

    https://www.kdnuggets.com/2017/n46.html

  • New Machine Learning and Data Science Books – Save 20%

    ...The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data... Read more. Statistical Reinforcement Learning: Modern Machine Learning Approaches Masashi Sugiyama Supplying an up-to-date and accessible introduction to the field,...

    https://www.kdnuggets.com/2015/06/crcpress-machine-learning-data-science-books.html

  • 2018 Year-in-Review: Machine Learning Open Source Projects & Frameworks

    ...l network fills those areas. The project currently has 6365 stars and 613 forks on GitHub.   TRFL TRFL pronounced as truffle, is used to program reinforcement learning agents in TensorFlow. To try your hand at this, follow the documentation.   Horizon Horizon is a platform for applied...

    https://www.kdnuggets.com/2018/12/2018-year-review-machine-learning-open-source-projects-frameworks.html

  • Top Data Science and Machine Learning Methods Used in 2017">Gold BlogTop Data Science and Machine Learning Methods Used in 2017

    ...ere is their share in 2017: Gradient Boosted Machines, 20.4% Conv Nets, 15.8% Recurrent Neural Networks (RNN), 10.5% Hidden Markov Models (HMM), 4.6% Reinforcement Learning, 4.2% Markov Logic Networks, 2.5% Generative Adversarial Networks (GAN), 2.3% The largest decline in share of usage was for...

    https://www.kdnuggets.com/2017/12/top-data-science-machine-learning-methods.html

  • Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science">Gold BlogData Science for Internet of Things (IoT): Ten Differences From Traditional Data Science

    ...u consider Cameras as sensors, there are many applications of Deep Learning algorithms such as CNNs for security applications, eg from hertasecurity. Reinforcement learning also has applications for IoT as I discussed in a post by Brandon Rohrer for Reinforcement Learning and Internet of Things 5)...

    https://www.kdnuggets.com/2016/09/data-science-iot-10-differences.html

  • Meet the World’s Leading AI & Deep Learning Experts

    ...s 20% off Early Bird discounted passes when you register before 3 May with the code KDNUGGETS .  DEEP LEARNING IN SAN FRANCISCO: What do ethics, reinforcement learning, and AI business applications have in common? By consolidating these summits, the co-located event will look at the most...

    https://www.kdnuggets.com/2019/04/rework-meet-worlds-leading-ai-deep-learning-experts.html

  • Top /r/MachineLearning Posts, August: Andrew Ng is back at it; Reinforcement Learning makes a splash; Fixing your ANN

    ....   Related: Top /r/MachineLearning Posts, July: Friendly Suggestions re: Coding Practices; Racist AI How-To Without Really Trying Top /r/MachineLearning Posts, June: NumPy Gets Funding; ML Cheat Sheets For All; Hot Dog or Not?!? Top /r/MachineLearning Posts, May: Deep Image Analogy; Stylized...

    https://www.kdnuggets.com/2017/09/top-reddit-machine-learning-august.html

  • Age of AI Conference 2018 – Day 1 Highlights

    ...rel et. al. Balaji concluded with some of the other areas of exciting research around using ideas from convergence of Nash equilibria, connections to Reinforcement Learning (RL) and control theory. Links: Learning in Implicit Generative Models https://arxiv.org/abs/1610.03483 Comparison of Maximum...

    https://www.kdnuggets.com/2018/02/age-ai-conference-2018-day-1.html

  • Top 10 Technology Trends of 2019

    ...ommunicating, and giving tasks to your refrigerator or lamp, as well as letting your car build the best routes and drive you there shortly.   7. Reinforcement learning and new architectures of neural networks will revolutionize prediction   The key idea of the neural networks is to create...

    https://www.kdnuggets.com/2019/02/top-10-technology-trends-2019.html

  • Attention and Memory in Deep Learning and NLP

    ...hat hasn't stopped attention mechanisms from becoming quite popular and performing well on many tasks. An alternative approach to attention is to use Reinforcement Learning to predict an approximate location to focus to. That sounds a lot more like human attention, and that’s what’s...

    https://www.kdnuggets.com/2016/01/attention-memory-deep-learning-nlp.html

  • My journey path from a Software Engineer to BI Specialist to a Data Scientist">Silver BlogMy journey path from a Software Engineer to BI Specialist to a Data Scientist

    ...MIT! 😀). Probability and Statistics: Statistics 110: Again, a great explanation, with good examples and also some problem sets to solve for. Machine Learning/Deep Learning: CS231N: It is amazing the way Stanford has published their classroom sessions online. I think Andrej Karpathy used to teach...

    https://www.kdnuggets.com/2019/09/journey-software-engineer-bi-data-scientist.html

  • Recreating Imagination: DeepMind Builds Neural Networks that Spontaneously Replay Past Experiences

    ...the world of AI. However, the team of DeepMind thinks that we have enough to get started.   Replay in AI   From the different fields of AI, reinforcement learning seems particularly well suited for the incorporation of experience replay mechanisms. A reinforcement learning agent, builds...

    https://www.kdnuggets.com/2019/10/recreating-imagination-deepmind-builds-neural-networks-spontaneously-replay-past-experiences.html

  • Afresh: Machine Learning Engineer

    ...or equivalent. Excellent programming and software design skills, particularly in Python. Strong understanding of machine learning, particularly deep learning, reinforcement learning, probabilistic models, Bayesian statistics. Expertise with the Python machine learning and deep learning stack:...

    https://www.kdnuggets.com/jobs/18/05-22-afresh-machine-learning-engineer.html

  • DeepLearningKit – Open Source Deep Learning Framework for Apple iOS, OS X

    …aper Deep Residual Learning for Image Recognition, or DeepMind’s (Google) AI for Atari games described in the papers Human-level control through deep reinforcement learning, Deep Reinforcement Learning with Double Q-Learning and Playing Atari with Deep Reinforcement Learning Other types of Deep…

    https://www.kdnuggets.com/2015/12/deeplearningkit-open-source-framework-apple-ios-osx.html

  • Research Guide for Neural Architecture Search

    ...; In this paper, the authors use a recurrent neural network (RNN) to generate the model descriptions of neural networks. The RNN is then trained with reinforcement learning in order to improve its accuracy on the validation set. The method achieves an error rate of 3.65 on the CIFAR-10 dataset....

    https://www.kdnuggets.com/2019/10/research-guide-neural-architecture-search.html

  • OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned

    ...) have started to leverage some of the principles of competition to influence learning behaviors in AI agents. Specifically, the field of multi-agent reinforcement learning(MARL) has been heavily influenced by the competitive and game-theoretic dynamics. Recently, researchers from OpenAI started by...

    https://www.kdnuggets.com/2019/10/openai-tried-train-ai-agents-play-hide-seek-instead-shocked-learned.html

  • The Emergence of Cooperative and Competitive AI Agents

    ...s to generate their own internal goals, such as capturing a flag. A two-tier process optimizes agents’ internal rewards directly for winning and uses reinforcement learning on the internal rewards to learn the agents’ policies. Agents operate at two timescales, fast and slow, which improves their...

    https://www.kdnuggets.com/2019/06/emergence-cooperative-competitive-ai-agents.html

  • Data Science for Beginners 1: The 5 questions data science answers

    ...I do now? uses reinforcement learning algorithms   The last question – What should I do now? – uses a family of algorithms called reinforcement learning. Reinforcement learning was inspired by how the brains of rats and humans respond to punishment and rewards. These algorithms learn from...

    https://www.kdnuggets.com/2016/07/brohrer-data-science-beginners-1-5-questions.html

  • SuperDataScience Podcast: Insights from the Founder of KDnuggets

    ...rney to data science, how KDnuggets started, why you should start honing your machine learning engineering skills, what's the future of data science, reinforcement learning, and a lot more. Here is the podcast: SDS 175: Insights from the Founder of KDnuggets Enjoy! Some excerpts: ... We spent the...

    https://www.kdnuggets.com/2018/07/superdatascience-podcast-insights-kdnuggets.html

  • Where AI is already rivaling humans

    ...s without any person in the driver’s position (but still somewhere inside the car) [108]. Most autonomous car driving software is based on supervised learning and reinforcement learning techniques as well as computer vision and image processing. Figure 2: Reaction Time While Driving Cars — Source...

    https://www.kdnuggets.com/2018/02/domains-ai-rivaling-humans.html

  • Top KDnuggets tweets, Feb 22-28: 50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus

    ...s to Learn Naive #Bayes Algorithm (with code in #Python) https://t.co/M5JDlK8jPd #MachineLearning https://t.co/LhfZbMMoVE Markov Decision Process and Reinforcement Learning https://t.co/8E5GQcbL4u #MachineLearning https://t.co/fK4LZ4eGy1 Winning Kaggle with 8GB RAM: Santander Product Recommendation...

    https://www.kdnuggets.com/2017/03/top-tweets-feb22-28.html

  • Anticipating the next move in data science – my interview with Thomson Reuters

    ...cause it started learning chess, Go and another game using zero human knowledge). It just played games with itself and used additional methods called reinforcement learning to improve. This program took only four hours of self-play to reach and exceed the world champion level in chess. The world...

    https://www.kdnuggets.com/2018/11/gps-anticipating-next-move-data-science.html

  • Predictive Analytics World for Manufacturing, Germany, Feb 2-3, Program highlights

    ...vised, which means that someone is labelling some data which gets fed into some algorithm. But as an alternative, there is a new star at the horizon: Reinforcement Learning (RL). This is a concept using an agent and an incentive system to train an agent. By taking the incentives the agent can learn...

    https://www.kdnuggets.com/2017/01/paw-predictive-analytics-world-manufacturing-germany-february-highlights.html

  • University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Medical Scheduling)

    ...erstanding in this area and an adaptation to our scheduling problem. Once this step is done we would like to apply deep neural network techniques, or reinforcement learning methods to the problem of obtaining optimal schedules. The second step concerns the learning part, from the sequence to the...

    https://www.kdnuggets.com/jobs/18/06-01-university-applied-sciences-western-switzerland-research-data-scientist-medical.html

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