This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community.
This book discusses the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. It describes... Læs mere
This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification.... Læs mere
This book redefines management practices using Artificial Intelligence by providing a new approach. It offers a detailed,... Læs mere
AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life... Læs mere
A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this... Læs mere
Based on the author’s experience teaching data science for more than 10 years, Mathematics and R Programming for Machine Learning reveals how machine learning algorithms do their magic and explains how logic can be implemented in code.
Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the... Læs mere
Edited by two of the leading experts in the field, this book provides a comprehensive reference book on feature engineering. The book provides a description of problems and applications for feature engineering, as well as its techniques, principles, issues, and challenges.