Learn what is deep Q-learning, how it relates to deep reinforcement learning, and then build your very first deep Q-learning model using Python!
Temporal difference learning is one of the core reinforcement learning concepts. Learn how it works, how it relates to Q-learning, & code it in Python!
We welcome Professor B. Ravidran to talk about his passion for reinforcement learning, the current state of the field, and how it all actually works!
In this article, learn how the algorithm behind DeepMind’s popular AlphaGo and AlphaGo Zero programs works – Monte Carlo Tree Search.
DataHack Radio #15: Exploring the Applications & Potential of Reinforcement Learning with Xander Steenbrugge
Introduction “If intelligence was a cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the …
A Technical Overview of AI & ML (NLP, Computer Vision, Reinforcement Learning) in 2018 & Trends for 2019
From Google’s BERT to Facebook’s PyTorch, 2018 was a HUGE year in ML. Find out what else made the news and what to look forward to in the new year!
This article is a collection of the most useful machine learning and deep learning GitHub repositories and Reddit discussions created in November 2018.
This detailed article covers an introduction to the Monte Carlo Method of learning using the popular OpenAI Gym library – with Python implementation!
This article lists down the most awesome machine learning and deep learning GitHub repositories and Reddit discussions from October 2018!
MADRaS is a multi-agent extension of Gym-TORCS and is open source, lightweight, easy to install, and has the OpenAI Gym API.