Автор: Группа авторов Название: Machine Learning: Algorithms and Applications
Книга Machine Learning:Algorithms and Applications написана для профессиональных специалистов в области машинного обучения, которые хотят внедрить решения для реальных задач машинного обучения. В ней представлен обзор различных приложений методов машинного и глубокого обучения с обсуждением новых подходов к архитектуре машинного обучения для конкретных приложений, а затем сравнение результатов с предыдущими
This book is not well known to you, so I'll try to describe it for you. Machine Learning Algorithms is aimed at current and well-intentioned machine learning enthusiasts who want to implement real-life solutions using machine learning methods. Each chapter introduces a unique approach to machine learning models for specific tasks and compares their results to previous ones using different algorithms and techniques. The book contains many examples that include statistics, pattern classification, neural networks and artificial intelligence among other topics, aiming to provide a comprehensive coverage of machine learning processes and approaches. Every learning algorithm in this book comes with clear instructions on how to turn them into computer programs, easing the learning process.
Электронная Книга «Machine Learning Algorithms and Applications» написана автором Группа авторов в году.
Минимальный возраст читателя: 0
Язык: Английский
ISBN: 9781119769248
Описание книги от Группа авторов
Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.
