Neural Network Programming with Python

Nonfiction, Computers, Advanced Computing, Natural Language Processing, Engineering, Neural Networks, Artificial Intelligence
Cover of the book Neural Network Programming with Python by Fabio. M. Soares, Rodrigo Nunes, Packt Publishing
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Author: Fabio. M. Soares, Rodrigo Nunes ISBN: 9781784392390
Publisher: Packt Publishing Publication: January 9, 2020
Imprint: Packt Publishing Language: English
Author: Fabio. M. Soares, Rodrigo Nunes
ISBN: 9781784392390
Publisher: Packt Publishing
Publication: January 9, 2020
Imprint: Packt Publishing
Language: English

Build smarter programs with the power of neural networks and the simplicity of Python

About This Book

  • Make your roots stronger in neural networks by this concept-rich yet highly practical guide; from single layer to multiple layers with the help of Python
  • Through this book, you will develop a strong background in neural networks, regardless of your level of previous knowledge in this subject
  • You will be able to implement solutions from scratch, so the whole process on foundations of neural network solution design will be paced by you

Who This Book Is For

This book is designed for novices as well as intermediate Python developers who have a statistical background and want to work with neural networks to get better results from complex data. It also contains enough food for thought for those who want to improve their skills in machine learning and deep learning.

What You Will Learn

  • See the latest innovations in the field
  • Become fluent in Python to develop neural networks solutions capable of solving complex and interesting tasks
  • Implement neural networks step-by-step
  • Solve your complex computational problems with the aid of neural networks and Python
  • The reader will be able to set up his/her neural network with ease, according to the objective he/she wants to apply.
  • The reader will be able to design time series based models using RNNs in Python.
  • Will be able to design high level solutions with CNNs in Python

In Detail

If you wish to solve your complex computational problem efficiently, neural networks come to the rescue. This book will teach you how to ace neural networks and solve your computational problems with Python—right from predicting to self-learning models—with ease. We start off with neural network design, then you'll build a solid foundational knowledge of how a neural network learns from data, and the principles behind it.

This book cover various types of neural networks including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but also see a generalization of these networks. With the help of practical examples and real-world use cases, you will learn to implement these neural networks in your applications.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Build smarter programs with the power of neural networks and the simplicity of Python

About This Book

Who This Book Is For

This book is designed for novices as well as intermediate Python developers who have a statistical background and want to work with neural networks to get better results from complex data. It also contains enough food for thought for those who want to improve their skills in machine learning and deep learning.

What You Will Learn

In Detail

If you wish to solve your complex computational problem efficiently, neural networks come to the rescue. This book will teach you how to ace neural networks and solve your computational problems with Python—right from predicting to self-learning models—with ease. We start off with neural network design, then you'll build a solid foundational knowledge of how a neural network learns from data, and the principles behind it.

This book cover various types of neural networks including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but also see a generalization of these networks. With the help of practical examples and real-world use cases, you will learn to implement these neural networks in your applications.

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