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Tag: Reinforcement Learning

An Intuitive Introduction to Reinforcement learning
Reinforcement learning (RL) is a trial and error form of learning in which an agent acting in a given environment learns to take optimal actions at every state it encounters in such an environment with the ultimate goal to increase/maximize a numerical reward function.
Evaluating Ray: Distributed Python for Massive Scalability
Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you are interested in additional insights, register for the upcoming Ray Summit. Introduction This post is for people making technology decisions, by which I mean data science …
Deep Reinforcement Learning
This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. It also covers using Keras to construct a deep Q-learning network that learns within a simulated …
Data Science Papers – Summer 2019 edition
Looking for a few academic data science papers to study? Here are a few I have found interesting. The are not all from the past 12 months, but I am including them anyhow. Cloud Programming Simplified: A Berkeley View on Serverless Computing (2019) – Serverless computing is very popular nowadays …
An introduction to Q-Learning: Reinforcement Learning
Learn about the basic concepts of reinforcement learning and implement a simple RL algorithm called Q-Learning.
Using Reinforcement Learning to Design a Better Rocket Engine
NASA [Public domain]In this blog, I’ll discuss how I worked collaboratively with various domain experts, using reinforcement learning to develop innovative solutions in rocket engine development. In doing so, I’ll demonstrate the application of ML techniques to the manufacturing industry and the role of the Machine Learning Product Manager.Machine learning …
Meta-Reinforcement Learning
The general trend in machine learning research is to stop fine-tuning models, and instead use a meta-learning algorithm that automatically finds the best architecture and hyperparameters. What about meta-reinforcement learning (meta-RL)? Meta-RL is just meta-learning applied to RL.
Free Reinforcement Learning Textbook
Reinforcement Learning: An Introduction by Rich Sutton and Andrew Barto was recently released on October 15, 2018. A free version is available online.
Themes and Conferences per Pacoid, Episode 2
Paco Nathan‘s column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI and Economics. Introduction Welcome back to our new monthly series! September has been the busiest part of “Conference Season” with excellent new material to review. Three themes jump out recently. …
How to Optimise Ad CTR with Reinforcement Learning
Understand the basics of reinforcement learning, what are the different types of reinforcement learning and use it to optimise CTR.