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Machine Learning Using TensorFlow Cookbook

You're reading from Machine Learning Using TensorFlow Cookbook Create powerful machine learning algorithms with TensorFlow

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781800208865

Length 416 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Authors (3):

Konrad Banachewicz

Luca Massaron

Alexia Audevart

View More author details

Table of Contents (15) Chapters

Preface

1. Getting Started with TensorFlow 2.x

2. The TensorFlow Way FREE CHAPTER

3. Keras

4. Linear Regression

5. Boosted Trees

Introduction

6. Neural Networks

7. Predicting with Tabular Data

8. Convolutional Neural Networks

9. Recurrent Neural Networks

10. Transformers

11. Reinforcement Learning with TensorFlow and TF-Agents

12. Taking TensorFlow to Production

13. Other Books You May Enjoy

14. Index

How TensorFlow works

Started as an internal project by researchers and engineers from the Google Brain team, initially named DistBelief, an open source framework for high performance numerical computations was released in November 2015 under the name TensorFlow (tensors are a generalization of scalars, vectors, matrices, and higher dimensionality matrices). You can read the original paper on the project here: http://download.tensorflow.org/paper/whitepaper2015.pdf. After the appearance of version 1.0 in 2017, last year, Google released TensorFlow 2.0, which continues the development and improvement of TensorFlow by making it more user-friendly and accessible.

Production-oriented and capable of handling different computational architectures (CPUs, GPUs, and now TPUs), TensorFlow is a framework for any kind of computation that requires high performance and easy distribution. It excels at deep learning, making it possible to create everything from shallow networks (neural networks...

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Authors (3)

Alexia Audevart

Alexia Audevart

Alexia Audevart, also a Google Developer Expert in machine learning, is the founder of datactik. She is a data scientist and helps her clients solve business problems by making their applications smarter. Her first book is a collaboration on artificial intelligence and neuroscience.

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Konrad Banachewicz

Konrad Banachewicz

Konrad Banachewicz is the author of the bestselling, The Kaggle Book and The Kaggle Workbook. He is a data science manager with experience stretching longer than he likes to ponder on. He holds a PhD in statistics from Vrije Universiteit Amsterdam, where he focused on problems of extreme dependency modeling in credit risk. He slowly moved from classic statistics towards machine learning and into the business applications world.

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Luca Massaron

Luca Massaron

Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.

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