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

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

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

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

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Overview

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.


Product Details

ISBN-13: 9781800206885
Publisher: Packt Publishing
Publication date: 02/08/2021
Sold by: Barnes & Noble
Format: eBook
Pages: 416
File size: 6 MB

About the Author

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.


Konrad Banachewicz holds a PhD in statistics from Vrije Universiteit Amsterdam. He is a lead data scientist at eBay and a Kaggle Grandmaster. He worked in a variety of financial institutions on a wide array of quantitative data analysis problems. In the process, he became an expert on the entire lifetime of a data product cycle.


Luca Massaron is a Google Developer Expert in machine learning with more than a decade of experience in data science. He is also the author of several best-selling books on AI and a Kaggle master who reached number 7 for his performance in data science competitions.

Table of Contents

Table of Contents
  1. Getting Started with TensorFlow 2.x
  2. The TensorFlow Way
  3. Keras
  4. Linear Regression
  5. Boosted Trees
  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
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