Statistical Learning Using Neural Networks
A Guide for Statisticians and Data Scientists with Python
- 234 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Statistical Learning Using Neural Networks
A Guide for Statisticians and Data Scientists with Python
About this book
Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students.
Key Features:
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- Discusses applications in several research areas
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- Covers a wide range of widely used statistical methodologies
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- Includes Python code examples
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- Gives numerous neural network models
This book covers fundamental concepts on Neural Networks including Multivariate Statistics Neural Networks, Regression Neural Network Models, Survival Analysis Networks, Time Series Forecasting Networks, Control Chart Networks, and Statistical Inference Results.
This book is suitable for both teaching and research. It introduces neural networks and is a guide for outsiders of academia working in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Fundamental Concepts on Neural Networks
- 3 Some Common Neural Network Models
- 4 Multivariate Statistics Neural Network Models
- 5 Regression Neural Network Models
- 6 Survival analysis and Other Networks
- A Command Reference
- Bibliography
- Index