Mastering TensorFlow 1.x
TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks.
Learn TensorFlow 2.0
What You'll Learn Review the new features of TensorFlow 2.0 Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples Who ...
TensorFlow 2.0 Quick Start Guide
With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.
Natural Language Processing with TensorFlow
After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks.
TensorFlow 2 Pocket Reference
Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset?
Deep Learning with TensorFlow
This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open ...
TinyML
With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.
Learn TensorFlow in 24 Hours
... tensorflow:Done running local_init_op. INFO:tensorflow:Saving checkpoints for 1 into train3/model.ckpt. INFO:tensorflow:loss = 83729.64, step = 1 INFO:tensorflow:global_step/sec: 72.5646 INFO:tensorflow:loss = 13909.657, step = 101 ...
Intelligent Mobile Projects with TensorFlow
... TensorFlow can be installed on MacOS , Ubuntu or Windows . We'll cover the steps to install TensorFlow 1.4 from its source on MacOS X El Capitan ( 10.11.6 ) , macOS Sierra ( 10.12 ... TensorFlow Chapter 1 Setting up TensorFlow on MacOS.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
TensorFlow For Dummies
With the guidance of this book, you can jump on board, too! TensorFlow For Dummies tames this sometimes intimidating technology and explains, in simple steps, how to write TensorFlow applications.
TensorFlow Reinforcement Learning Quick Start Guide
With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.
Hands-On Computer Vision with TensorFlow 2
This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks.
Optimizing Machine Learning Pipelines: Advanced Techniques with TensorFlow and Kubeflow
... TensorFlow Serving , preparing it for handling inference requests . With TensorFlow Serving now running , your models are accessible via RESTful APIs or gRPC endpoints , allowing for efficient and scalable model deployment in production ...
Machine Learning Projects for Mobile Applications
We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks.
Learning TensorFlow
Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow.
Pro Deep Learning with TensorFlow
This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book.
Deep Learning with TensorFlow and Keras
This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical ...
What's New in TensorFlow 2.0
This book will help you understand and utilize the latest TensorFlow features.