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. Additional ISBNs 1138364509, 0429431295, 9781138364509, 9780429431296Statistical Learning Using Neural Networks: A Guide for Statisticians and Data Scientists with Python 1st Edition is written by Basilio de Braganca Pereira; Calyampudi Radhakrishna Rao; Fabio Borges de Oliveira and published by Chapman & Hall. ISBNs for Statistical Learning Using Neural Networks are 9780429775543, 0429775547 and the print ISBNs are 9781138364509, 1138364509. Additional ISBNs include 1138364509, 0429431295, 9781138364509, 9780429431296.