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Machine Learning Using TensorFlow Cookbook
Machine Learning Using TensorFlow Cookbook

Machine Learning Using TensorFlow Cookbook: Create powerful machine learning algorithms with TensorFlow

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Profile Icon Alexia Audevart Profile Icon Konrad Banachewicz Profile Icon Luca Massaron
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$25.19 $27.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (16 Ratings)
eBook Feb 2021 416 pages 1st Edition
eBook
$25.19 $27.99
Paperback
$40.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Alexia Audevart Profile Icon Konrad Banachewicz Profile Icon Luca Massaron
Arrow right icon
$25.19 $27.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (16 Ratings)
eBook Feb 2021 416 pages 1st Edition
eBook
$25.19 $27.99
Paperback
$40.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$25.19 $27.99
Paperback
$40.99
Subscription
Free Trial
Renews at $19.99p/m

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Machine Learning Using TensorFlow Cookbook

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Key benefits

  • Deep Learning solutions from Kaggle Masters and Google Developer Experts
  • Get to grips with the fundamentals including variables, matrices, and data sources
  • Learn advanced techniques to make your algorithms faster and more accurate

Description

The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. Dive into recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google’s machine learning library, TensorFlow. This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You’ll discover real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and regression. Explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be used to solve computer vision and natural language processing (NLP) problems. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios.

Who is this book for?

If you are a data scientist or a machine learning engineer, and you want to skip detailed theoretical explanations in favor of building production-ready machine learning models using TensorFlow, this book is for you. Basic familiarity with Python, linear algebra, statistics, and machine learning is necessary to make the most out of this book.

What you will learn

  • Take TensorFlow into production
  • Implement and fine-tune Transformer models for various NLP tasks
  • Apply reinforcement learning algorithms using the TF-Agents framework
  • Understand linear regression techniques and use Estimators to train linear models
  • Execute neural networks and improve predictions on tabular data
  • Master convolutional neural networks and recurrent neural networks through practical recipes

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 08, 2021
Length: 416 pages
Edition : 1st
Language : English
ISBN-13 : 9781800206885
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Product Details

Publication date : Feb 08, 2021
Length: 416 pages
Edition : 1st
Language : English
ISBN-13 : 9781800206885
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Tools :

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Frequently bought together


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Total $ 137.97
TensorFlow 2.0 Computer Vision Cookbook
$45.99
Machine Learning Using TensorFlow Cookbook
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TensorFlow 2 Reinforcement Learning Cookbook
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Total $ 137.97 Stars icon

Table of Contents

14 Chapters
Getting Started with TensorFlow 2.x Chevron down icon Chevron up icon
The TensorFlow Way Chevron down icon Chevron up icon
Keras Chevron down icon Chevron up icon
Linear Regression Chevron down icon Chevron up icon
Boosted Trees Chevron down icon Chevron up icon
Neural Networks Chevron down icon Chevron up icon
Predicting with Tabular Data Chevron down icon Chevron up icon
Convolutional Neural Networks Chevron down icon Chevron up icon
Recurrent Neural Networks Chevron down icon Chevron up icon
Transformers Chevron down icon Chevron up icon
Reinforcement Learning with TensorFlow and TF-Agents Chevron down icon Chevron up icon
Taking TensorFlow to Production Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(16 Ratings)
5 star 93.8%
4 star 6.3%
3 star 0%
2 star 0%
1 star 0%
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Marleen Mar 06, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The first three chapters of this book provide an introduction to TensorFlow 2 (TF) in general as well as some TF specific operations/syntax which is very handy to know! And the third chapter on the introduction is related to Keras.Then the book continues with a chapter on Linear Regression. I got a bit confused here because this chapters also discusses Logistic Regressions and others, which are all known as linear models, I just didn't expect to find logistic regression in here - a pleasant surprise!The chapter on Boosted Trees was missing structure I find. This one, the Transformers chapter and the RL chapter are definitely for readers that know how those models work and are just looking for implementation advise using TF.Then finally, my favourite chapters: various Neural Networks and the Deploying models to PRD. Those pages were filled with very well designed examples and I enjoyed going through them a lot!Therefore overall, this book will definitely help you understand how to use TensorFlow, but if you expect to learn the models used as well, you might need an additional book with more theory on e.g. Reinforcement Learning.The examples accompanying the book are all very straight forward and easy to follow along. This book is definitely a buy if you buy it for the purpose of learning TF!!(Site-note: I wish for other RL examples in books that have chapters on RL. It seems like many use the same.)
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Samuel de Zoete Jul 20, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Getting Ready! How to do it...! How it works...!" is the structure of the recipes in the book and it works for me. The explanations are short and straight to the point, I personally love when a learning book is concise. Plenty of resource suggestions if deep dive is necessary or brushing up on certain knowledge, e.g. Matrix Computations. I would suggest, download the code from GitHub and use Google Colab with the book. I read the book from my iPad and code on my laptop, it's perfect for me this way.When reading the book it provided me a good reference and framework how to setup, design and use TensorFlow. I usually use the Keras Interface, beyond that, it seems all a bit 'difficult', but this book gives me the confidence that directly using TF is now an option when it's needed.
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Vicky Apr 29, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is an extraordinary asset for those keen on applying complex data computations using TensorFlow.It is somewhat light on detailed theoretical explanations but provides resourceful insights for building production-ready modules in real-world scenarios. I would recommend it if you are either already familiar with basic ML theory and the math background or if you have a software engineering background and are simply looking to implement an ML solution with Tensorflow.
Amazon Verified review Amazon
Mihai Maruseac Apr 23, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really enjoyed reading this book. I tried to judge it based on how someone new to the Machine Learning field would feel when reading it as well as on how someone with deep expertise would. I am happy to report that I think both types of readers would enjoy reading the book.The book is a collection of recipes on how to solve various ML tasks using TF. It uses TF 2.x, the more modern version of TensorFlow but still has mentions for relevant TF 1.x features, as they are needed in some places of the prose.Each recipe starts from the first line of code and finishes with a fully working example, including output documentation. There are also explanations for the output and sometimes even suggestions for different avenues of experimentation.The first few chapters are very introductory. A reader would learn how to use raw TF API to create an ML model, then how to become better and more efficient by using higher level APIs, such as Keras and tf.data (and Estimators but these are TF 1.x features, so the corresponding chapter should be read with a view on the past history of TF).The last part of the book focuses on solutions for different ML tasks. Image processing, NLP, reinforcement learning, are all topics that are touched and presented at a reasonable level.
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JOSET Mar 20, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Really interesting and relevant book for the use of Temsorflow!Well done to the writers and Alexia!
Amazon Verified review Amazon
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