Pytorch Deep Learning by Example (2nd Edition): Grasp deep Learning from scratch like AlphaGo Zero within 40 days

By Benjamin Young

Summary

Pytoch is a quite powerful, flexible and yet popular deep learning framework, but the learning curve could be steep if you do not have much deep learning background or are simply from Keras background. This book will ease the pain and help you learn and grasp the latest PyTorch deep learning technology from ground zero with many interesting real-world examples. It could also be used as a quick guide on how to use and understand deep learning in real life.

Free lifetime upgrade ( for an electronic copy ) as the book has been and will be frequently updated according to readers' feedbacks. Previous buyers, please feel free to contact the author for free update ( electronic copy ).

Description

Artificial Intelligence (AI), Machine Learning especially Deep Learning has made tremendous progress in recent years. It starts to spread to all industries.

Unless you are a refresh graduated student with AI/deep learning major, many of us do not have a formal machine learning/deep learning training before, so it is time to keep updated with latest technology.

Pytoch is a quite powerful, flexible and yet popular deep learning framework, but the learning curve could be steep if you do not have much deep learning background. This book will easy the pain and help you learn and grasp latest pytorch deep learning technology from ground zero with many interesting real world examples. It covers many state-of-art deep learning technologies, e.g.: Convoluational neural network (CNN), Recurrent neural network (RNN), Seq2Seq model, word emedding, Connectionist temporal calssification (CTC ), Auto-encoder, Dynamic Memrory Network (DMN), Deep-Q-learning(DQN/DDQN), Monte Carlo Tree search (MCTS), Alphago/Alphazero etc. This book could also be used as a quick guide on how to use and understand deep learning in the real life.

Readers should have basic knowledge of python, scripting etc. Any constructive feedback is welcome.

Table of Contents

IntroductionWhat is deep learningDeep neural network basic conceptsDeep learning development environmentsPython and Tensor basicPytorch deep learning basicMNIST CNN example: A deep dive of how to handle image dataPre-trained model, transfer learning and fine-tuningRecurrent neural network - how to handle sequences dataNatural Langauge ProcessingOptical character recognitionAudio processing, speech processingAutoencoder networkDeep reinforcement learningLearning from scratch (self-play) AlphaZeroHow to deploy deep learning model.

Note:

a keras/tensorflow version of this book Deep Learning with Keras from Scratch could be bought at https: //www.amazon.com/Learning-Keras-Scratch-Benjamin-Young/dp/1091838828

• Format: Paperback
• Language: English
• ISBN: 108954989X
• ISBN13: 9781089549895
• Release Date: August 2019
• Publisher: Independently Published
• Length: 416 Pages
• Weight: 1.81 lbs.
• Dimensions: 0.8" x 8.0" x 10.0"