Deep Learning with Keras from Scratch (9781091838826)



Summary

Keras is a very popular, easy to use, yet powerful deep learning framework that promotes a simple and intuitive syntax. But if you do not have much deep learning background, you will find difficulties to really understand the keras codes and have obstacles to implement real life deep learning projects effectively in keras. This book will easy the pain and help you learn and grasp deep learning technology from ground zero with many interesting real world examples implemented in keras/tensorflow by using bare-minimum math. It could also be used as a quick guide on how to use and understand deep learning in the real life.

Description

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

Quote from Andrew Ng, a famous AI researcher: "AI is the new electricity. About 100 years ago, electricity transformed every major industry. AI has advanced to the point where it has the power to transform every major sector in coming years."

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.

This book will help you learn and grasp deep learning technology from ground zero with many interesting real world examples using python/keras/tensorflow. 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. The books 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.

Free lifetime upgrade for later editions ( as an electronic copy ). Please contact author for this.

Table of Contents

IntroductionWhat is deep learningDeep neural network basic conectpsPython and NumPy basicDeep learning development environmentsMNIST 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

Pytorch version of this book (Pytorch Deep Learning by Example) could be found at: https: //www.amazon.com/Pytorch-Learning-Example-Benjamin-Young/dp/1096343584


Product details

  • Paperback | 406 pages
  • 203 x 254 x 21mm | 803g
  • English
  • 1091838828
  • 9781091838826


Download Deep Learning with Keras from Scratch (9781091838826).pdf, available at book018.dynamic-dns.net for free.

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