TensorFlow 1.x Deep Learning Cookbook
Deep Neural Networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning, and implement different deep learning networks with easy to follow independent recipes.
Offered by
Difficulty Level
Intermediate
Completion Time
17h52m
Language
English
About Book
Who Is This Book For?
This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful.
TensorFlow 1.x Deep Learning Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 17h52m total length
Initial steps in Tensorflow 1.x
Regression
Neural Networks: Perceptrons
Convolutional Neural Network
CNN in Action
Recurrent Neural Networks
Unsupervised Learning
Autoencoders
Reinforcement Learning
Tensorflow Mobile
Generative Adverasial Networks
Deep Learning on Cloud
Appendix
Appendix B : Learning to Learn with AutoML (or what is Meta-Learning)
Related Resources
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