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TensorFlow 2 Reinforcement Learning Cookbook

intelligence applications. Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers;

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Machine Learning Using TensorFlow Cookbook

Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and more Key Features Deep Learning;

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Reinforcement Learning for Finance

This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the TensorFlow;

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Reinforcement Learning

starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage;

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Applied Reinforcement Learning with Python

topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. Applied Reinforcement;

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TensorFlow Machine Learning Cookbook

, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands;

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Python Reinforcement Learning Projects

TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and;

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TensorFlow 1.x Deep Learning Cookbook

and implement tricky neural networks using Google's TensorFlow 1.x * An easy-to-follow guide that lets you explore reinforcement learning;

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TensorFlow for Deep Learning From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If;

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TensorFlow Machine Learning Cookbook

Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook;

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Deep Reinforcement Learning with Python

deep reinforcement learning implementation using popular deep learning frameworks such as TensorFlow and PyTorch. In the end, you'll;

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Artificial Intelligence, Machine Learning, and Deep Learning

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will;

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Deep Learning Projects Using TensorFlow 2

Work through engaging and practical deep learning projects using TensorFlow 2.0.;

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Deep Learning with TensorFlow 2 and Keras

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;

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Tensorflow 2

learning, linear and logical regression, etc. Covers TensorFlow 2 and previous versions that run with TF2. Includes companion files with source;

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Beginning Deep Learning with TensorFlow

TensorFlow 2 and Keras.;

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Hands-On Reinforcement Learning with Python

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the;

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TensorFlow Deep Learning Projects

Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep;

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Python Machine Learning

Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning;

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Python Reinforcement Learning

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features Your entry;

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Advanced Deep Learning with Keras

libraries. A new second edition, updated for 2020 and featuring TensorFlow 2 and coverage of unsupervised learning using mutual information, object;

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TensorFlow

reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will;

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TensorFlow 2 x in the Colaboratory Cloud

well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow;

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State-of-the-Art Deep Learning Models in TensorFlow

Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab;

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Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn

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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity Key Features Learn how to;

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TensorFlow 2.0 Quick Start Guide

book is forData scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will;

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