McClure TensorFlow Machine Learning Cookbook

Over 60 practical recipes to help you master Google's TensorFlow machine learning library
1. Auflage 2024
ISBN: 978-1-78646-630-3
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 370 Seiten

Explore machine learning concepts using the latest numerical computing library — TensorFlow — with the help of this comprehensive cookbookKey Features - [*] Your quick guide to implementing TensorFlow in your day-to-day machine learning activities
- [*] Learn advanced techniques that bring more accuracy and speed to machine learning
- [*] Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow
Book DescriptionTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow. This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production. What you will learn - * Become familiar with the basics of the TensorFlow machine learning library
- * Get to know Linear Regression techniques with TensorFlow
- * Learn SVMs with hands-on recipes
- * Implement neural networks and improve predictions
- * Apply NLP and sentiment analysis to your data
- * Master CNN and RNN through practical recipes
- * Take TensorFlow into production
Who this book is forThis book is ideal for data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.

Autoren/Hrsg.

McClure, Nick McClure

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik

Inhaltsverzeichnis

Table of Contents - Getting started with TensorFlow
- The Tensorflow Way
- Linear Regression
- Support Vector Machines
- Nearest Neighbor Methods
- Neural Networks
- Natural Language Processing
- Convolutional Neural Networks
- Reccurrent Neural Networks
- Taking TensorFlow to Production
- More with TensorFlow

Über Autor(innen)

McClure Nick :

Nick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow Group and Caesar's Entertainment Corporation. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict and Saint John's University. He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence. Nick occasionally puts his thoughts and musings on his blog or through his Twitter account, @nfmcclure.