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Hands-On Automated Machine Learning

You're reading from   Hands-On Automated Machine Learning A beginner's guide to building automated machine learning systems using AutoML and Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788629898
Length 282 pages
Edition 1st Edition
Languages
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Authors (2):
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Umit Mert Cakmak Umit Mert Cakmak
Author Profile Icon Umit Mert Cakmak
Umit Mert Cakmak
Sibanjan Das Sibanjan Das
Author Profile Icon Sibanjan Das
Sibanjan Das
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to AutoML FREE CHAPTER 2. Introduction to Machine Learning Using Python 3. Data Preprocessing 4. Automated Algorithm Selection 5. Hyperparameter Optimization 6. Creating AutoML Pipelines 7. Dive into Deep Learning 8. Critical Aspects of ML and Data Science Projects 9. Other Books You May Enjoy

Overview of neural networks

The best definition of a neural network is provided by an inventor, Dr. Robert Hecht-Nielsen, one of the first neurocomputer scientists, in Neural Network Primer: Part I by Maureen Caudill, AI Expert, Feb. 1989:

...a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.

The fundamental building blocks of neural networks are neurons, and they are organized in different layers. The tiered architecture has the neurons in each layer connected to neurons in the next layer. A neural network has, at a minimum, three layers. The input layer is connected to one or more hidden layers, where the connection is established through a system of weighted links. The last hidden layer is connected to the output layer which produces the results of a task...

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