Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
TensorFlow 1.x Deep Learning Cookbook

You're reading from   TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Arrow left icon
Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788293594
Length 536 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. TensorFlow - An Introduction 2. Regression FREE CHAPTER 3. Neural Networks - Perceptron 4. Convolutional Neural Networks 5. Advanced Convolutional Neural Networks 6. Recurrent Neural Networks 7. Unsupervised Learning 8. Autoencoders 9. Reinforcement Learning 10. Mobile Computation 11. Generative Models and CapsNet 12. Distributed TensorFlow and Cloud Deep Learning 13. Learning to Learn with AutoML (Meta-Learning) 14. TensorFlow Processing Units

Introduction

Regression is one of the oldest and yet quite powerful tools for mathematical modelling, classification, and prediction. Regression finds application in varied fields ranging from engineering, physical science, biology, and the financial market to social sciences. It is the basic tool in the hand of a data scientist.

Regression is normally the first algorithm that people in machine learning work with. It allows us to make predictions from data by learning the relationship between the dependent and independent variables. For example, in the case of house price estimation, we determine the relationship between the area of the house (independent variable) and its price (dependent variable); this relationship can be then used to predict the price of any house given its area. We can have multiple independent variables impacting the dependent variable. Thus, there are two...

You have been reading a chapter from
TensorFlow 1.x Deep Learning Cookbook
Published in: Dec 2017
Publisher: Packt
ISBN-13: 9781788293594
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image