Statistical Learning Using Neural Networks: A Guide for Statisticians and Data Scientists with Python

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

Discusses applications in several research areas Covers a wide range of widely used statistical methodologies Includes Python code examples 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.

Book Details

• Authors: Basilio de Braganca Pereira, Calyampudi Radhakrishna Rao, Fabio Borges de Oliveira
• Publisher: Chapman & Hall
• eBook ISBN: 9780429775543, 0429775547
• Print ISBN: 9781138364509, 1138364509
• Other ISBNs: 0429431295, 9780429431296