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How to Get Started with Deep Reinforcement Learning on a Variety of Use Cases
Editor’s note: Maggie is a speaker for ODSC APAC 2021. Check out her talk, “How to Get Started With Deep Reinforcement Learning on a Variety of Use Cases?” there! I, like many others, first heard of reinforcement learning (RL) in the context of games. I watched... Read more
The Paladin, the Cleric, and the… Reinforcement Learning?
Data science and artificial intelligence are everywhere. So are video games. It’s no surprise that it was only a matter of time until people started getting creative with combining the two in unique ways. And no, I’m not talking about improving in-game AI (because clearly, Skyrim... Read more
Up Your Game with OpenAI Gym Reinforcement Learning 
Reinforcement learning is currently one of the most promising methods in machine learning and deep learning.  OpenAI Gym is one of the most popular toolkits for implementing reinforcement learning simulation environments. Here’s a quick overview of the key terminology around OpenAI Gym.  https://gym.openai.com/videos/2019-10-21--mqt8Qj1mwo/LunarLander-v2/original.mp4 Source What is... Read more
Ten Trending Data Science Tools in 2021
The fields of data science and artificial intelligence see constant growth. As more companies and industries find value in automation, analytics, and insight discovery, there comes a need for the development of new tools, frameworks, and libraries to meet increased demand. There are some tools that... Read more
Reinforcement Learning: The Next Frontier
Deep Learning in recent years has touched many milestones – convolutional neural networks have surpassed human performance in tasks like object detection, image classification. Transformers are providing awesome results in natural language-based tasks. While these are outstanding achievements, these methods suffer from the fact that they... Read more
First Steps Before Applying Reinforcement Learning for Trading
There are many methodologies in algorithmic trading — from automated trade entry and close points based on technical and fundamental indicators to intelligent forecasts and decision making using complex maths and, of course, artificial intelligence. Reinforcement learning here stands out as a Holy Grail — no... Read more
Teaching KNIME to Play Tic-Tac-Toe
In this blog post I want to introduce some basic concepts of reinforcement learning, some important terminology, and show a simple use case where I create a game playing AI in KNIME Analytics Platform. After reading this, I hope you’ll have a better understanding of the... Read more
How to Make Sense of the Reinforcement Learning Agents? What and Why I Log During Training and Debug
Based on simply watching how an agent acts in the environment, it is hard to tell anything about why it behaves this way and how it works internally. That’s why it is crucial to establish metrics that tell WHY the agent performs in a certain way.... Read more
Reinforcement Learning with Ray RLlib
Why Reinforcement Learning? In reinforcement learning (RL), an agent tries to maximize a reward while interacting with an environment. The agent observes the state of the environment, takes an action and observes the reward received (if any) and the new state. Then the agent takes the... Read more
Explore Fundamental Concepts of Reinforcement Learning
This article is an excerpt from the book Mastering Machine Learning Algorithms, Second Edition by Giuseppe Bonaccorso, a newly updated and revised edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems. This article helps you understand... Read more