You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838826994

Edition2nd Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

Data

In our example, we will use the Russian stock market prices from the period of 2015-2016, which are placed in Chapter08/data/ch08-small-quotes.tgz and have to be unpacked before model training.

Inside the archive, we have CSV files with M1 bars, which means that every row in each CSV file corresponds to a single minute in time, and price movement during that minute is captured with four prices: open, high, low, and close. Here, an open price is the price at the beginning of the minute, high is the maximum price during the interval, low is the minimum price, and the close price is the last price of the minute time interval. Every minute interval is called a bar and allows us to have an idea of price movement within the interval. For example, in the YNDX_160101_161231.csv file (which has Yandex company stocks for 2016), we have 130k lines in this form:

<DATE>,<TIME>,<OPEN>,<HIGH>,<LOW>,<CLOSE>,<VOL>
20160104,100100,1148.9,1148.9,1148...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Data

Unlock this book and the full library FREE for 7 days

Author (1)

TensorFlow Reinforcement Learning Quick Start Guide

Deep Reinforcement Learning with Python

Hands-On Intelligent Agents with OpenAI Gym

Hands-On Q-Learning with Python

PyTorch 1.x Reinforcement Learning Cookbook

TensorFlow 2 Reinforcement Learning Cookbook

Reinforcement Learning Algorithms with Python

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