Statistical learning using neural networks : a guide for statistical and data scientists /
Basilio de Braganca Pereira, Calyampudi Radhakrishna Rao and Fabio Borges de Oliveira
- Boca Raton CRC Press 2022
- 233p.
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.
9781032335933
Statistics - Data Processing Statistics Multivariate analysis - Data Processing Neural networks (Computer Science) Computational learning theory Statistics - Methodology Python (Computer Programming Language)