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Neural Network Essentials

Neural networks are the core of all AI algorithms, and today, deep neural networks are used in tasks ranging from image recognition and object detection to natural language processing and generation. After dissecting the basic building blocks that form a neural network and the principles of how they work, this Refcard delves into neural architecture types and their respective uses, neural network chips, and model optimization techniques at a high level.
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Book Review: Foundations of Deep Reinforcement Learning, by Laura Graesser and Wah Loon Keng

Deep Reinforcement Learning is a somewhat new field within Machine Learning or Artificial Intelligence (you may pick your favorite term between these two, even if they’re not strictly the same), which combines Deep Learning and Reinforcement Learning and is based on the general idea that an agent can learn by observing its actions and their consequences. No, it is not a return to John B. Watson and B. F. Skinner’s behavioral psychology. We are talking, instead, about a set of pretty advanced machine learning algorithms that, when properly mastered, allow computers to achieve remarkable results in some complex tasks. That’s what this book is about, so let’s dive in…

Book Structure and Contents

Foundations of Deep Reinforcement Learning - Theory and Practice in Python begins with a brief preliminary chapter, which serves to introduce a few concepts and terms that will be used throughout all the other chapters: agent, state, action, objective, reward, reinforcement, policy, value function, model, trajectory, transition.

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Trading Strategies Using Deep Reinforcement Learning

The purpose of this post is to expose some results after creating a trading bot based on Reinforcement Learning that is capable of generating a trading strategy and at the same time to share a possible architecture for an agent and the features of the dataset that was used, furthermore to share detail about the problems faced.

First, we need to understand the problem, so let’s talk about Trading.