Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please send contact us.
Compatible Devices: Can be read on any devices
and related topics, this book provides a broad survey of the field.
Generous exercises and examples give students a firm grasp of the
concepts and techniques of this rapidly developing, challenging subject.
Introduction to Machine Learning synthesizes and clarifies
the work of leading researchers, much of which is otherwise available
only in undigested technical reports, journals, and conference proceedings.
Beginning with an overview suitable for undergraduate readers, Kodratoff
establishes a theoretical basis for machine learning and describes
its technical concepts and major application areas. Relevant logic
programming examples are given in Prolog.
Introduction to Machine Learning is an accessible and original
introduction to a significant research area.

Advanced Business Analytics eBook
Arquitectura habitacional Vol I eBook
Concepts in Neonatal Nutrition, An Issue of Clinics in Perinatology eBook
Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th Edition eBook
The Age of Surveillance Capitalism eBook
International Organizational Behavior eBook
Network Security Essentials eBook
Microsoft Office Publisher 2007 Step by Step eBook
Invitation to Public Speaking Handbook eBook
Becoming a Helper, 7th Edition eBook
The United States Healthcare System: Overview, Driving Forces, and Outlook for the Future eBook
Sex at Dawn eBook
The Complete Project Management Office Handbook eBook
Geometric Dimensioning and Tolerancing eBook
Bring Your Own Devices (BYOD) Survival Guide eBook
Access 2007 eBook 


Reviews
There are no reviews yet.