eBook - PDF

Machine Learning

Name: Machine Learning
Author: Ryszard S. Michalski,Jaime G. Carbonell,Tom M. Mitchell

An Artificial Intelligence Approach (Volume I)

Ryszard S. Michalski,

Jaime G. Carbonell,

Tom M. Mitchell,

572 pages
English
PDF
Available on iOS & Android

eBook - PDF

Machine Learning

An Artificial Intelligence Approach (Volume I)

Ryszard S. Michalski,

Jaime G. Carbonell,

Tom M. Mitchell,

About this book

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs—particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV and V discuss learning from observation and discovery, and learning from instruction, respectively. Part VI presents two studies on applied learning systems—one on the recovery of valuable information via inductive inference; the other on inducing models of simple algebraic skills from observed student performance in the context of the Leeds Modeling System (LMS). This book is intended for researchers in artificial intelligence, computer science, and cognitive psychology; students in artificial intelligence and related disciplines; and a diverse range of readers, including computer scientists, robotics experts, knowledge engineers, educators, philosophers, data analysts, psychologists, and electronic engineers.

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Yes, you can access Machine Learning by Ryszard S. Michalski,Jaime G. Carbonell,Tom M. Mitchell in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.