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

Tensors

A tensor is the fundamental building block of all DL toolkits. The name sounds rather mystical, but the underlying idea is that a tensor is a multi-dimensional array. Using the analogy of school math, one single number is like a point, which is zero-dimensional, while a vector is one-dimensional like a line segment, and a matrix is a two-dimensional object. Three-dimensional number collections can be represented by a parallelepiped of numbers, but they don't have a separate name in the same way as a matrix. We can keep the term "tensor" for collections of higher dimensions.

Another thing to note about tensors used in DL is that they are only partially related to tensors used in tensor calculus or tensor algebra. In DL, a tensor is any multi-dimensional array, but in mathematics, a tensor is a mapping between vector spaces, which might be represented as a multi-dimensional array in some cases, but has much more semantical payload behind it. Mathematicians usually...

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

Tensors

Unlock this book and the full library FREE for 7 days

Author (1)

TensorFlow Reinforcement Learning Quick Start Guide

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