
Neural Network Programming with Python
Packt Publishing
Published on 28. April 2017
Book
Paperback/Softback
430 pages
978-1-78439-821-7 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 191 mm
ISBN-13
978-1-78439-821-7 (9781784398217)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Fabio Soares holds a master's degree in Applied Computing by UFPA and is currently a PhD candidate at the same university. He has been designing Neural Networks solutions since 2004 and has developed applications of this technique on several fields ranging from telecommunications to chemistry process modelling, and his research topics cover supervised learning for data-driven modelling.
He was the author of Neural Network Programming with Java, Packt Publishing ( https://www.packtpub.com/networking-and-servers/neural-network-programming-java).
He also authored a book on Neural Networks ( http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=5596645).
Fabio is self-employed, and offers services such as IT infrastructure management as well as database administration for a number of small and medium-sized companies in Northern Brazil. He has also experience as a lecturer, having worked at the Federal Rural University of Amazon and Faculty of Castanhal, both in the state of Para, teaching subjects involving programming and artificial intelligence.
Fabio Soares has published a number of works, many of them available in English, all including the topics of artificial intelligence applied to some problem. Publications include Conference Proceedings such as the TMS (The Minerals Materials and Minerals Society) Light Metals, and the Intelligent Data Engineering and Automated Learning. Fabio also has published two book chapters for Intech. Here are few links to his work:
http://onlinelibrary.wiley.com/doi/10.1002/9781119274780.ch102/summary
http://onlinelibrary.wiley.com/doi/10.1002/9781118663189.ch125/summary
http://www.intechopen.com/books/fuzzy-logic-tool-for-getting-accurate-solutions/a-simple-fuzzy-system-applied-to-predict-default-rate
http://www.intechopen.com/books/fuzzy-logic-controls-concepts-theories-and-applications/fuzzy-control-applied-to-aluminium-smelting-process
http://link.springer.com/chapter/10.1007%2F978-3-642-32639-4_36
http://link.springer.com/chapter/10.1007%2F978-3-642-32639-4_37
You can find him on LinkedIn at https://br.linkedin.com/in/fabio-soares-b68b1a2. At present, Rodrigo is Software Developer at Aero Informatica, where he has worked for almost 3 years.
He worked at C & S Systems for 4 months and as a programmer at ZTEC for a year and a half.
He is an expert in Python, which he has worked with for more than 7 years. Fabio Soares has worked with him and can attest his capacity and competence.
Rodrigo has worked on projects with Python and Arduino. These include turning electricity on and off, verifying energy spending, and voice commands to Arduino.
Suggestion projects for purchases in markets , comparison of price across Several projects in many markets.
Projects of financial management systems.
Project on voice recognition - http://sigmabyte.blogspot.in/
He was the author of Neural Network Programming with Java, Packt Publishing ( https://www.packtpub.com/networking-and-servers/neural-network-programming-java).
He also authored a book on Neural Networks ( http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=5596645).
Fabio is self-employed, and offers services such as IT infrastructure management as well as database administration for a number of small and medium-sized companies in Northern Brazil. He has also experience as a lecturer, having worked at the Federal Rural University of Amazon and Faculty of Castanhal, both in the state of Para, teaching subjects involving programming and artificial intelligence.
Fabio Soares has published a number of works, many of them available in English, all including the topics of artificial intelligence applied to some problem. Publications include Conference Proceedings such as the TMS (The Minerals Materials and Minerals Society) Light Metals, and the Intelligent Data Engineering and Automated Learning. Fabio also has published two book chapters for Intech. Here are few links to his work:
http://onlinelibrary.wiley.com/doi/10.1002/9781119274780.ch102/summary
http://onlinelibrary.wiley.com/doi/10.1002/9781118663189.ch125/summary
http://www.intechopen.com/books/fuzzy-logic-tool-for-getting-accurate-solutions/a-simple-fuzzy-system-applied-to-predict-default-rate
http://www.intechopen.com/books/fuzzy-logic-controls-concepts-theories-and-applications/fuzzy-control-applied-to-aluminium-smelting-process
http://link.springer.com/chapter/10.1007%2F978-3-642-32639-4_36
http://link.springer.com/chapter/10.1007%2F978-3-642-32639-4_37
You can find him on LinkedIn at https://br.linkedin.com/in/fabio-soares-b68b1a2. At present, Rodrigo is Software Developer at Aero Informatica, where he has worked for almost 3 years.
He worked at C & S Systems for 4 months and as a programmer at ZTEC for a year and a half.
He is an expert in Python, which he has worked with for more than 7 years. Fabio Soares has worked with him and can attest his capacity and competence.
Rodrigo has worked on projects with Python and Arduino. These include turning electricity on and off, verifying energy spending, and voice commands to Arduino.
Suggestion projects for purchases in markets , comparison of price across Several projects in many markets.
Projects of financial management systems.
Project on voice recognition - http://sigmabyte.blogspot.in/