Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

Kevin P. Murphy


Today's Web-enabled deluge of digital information demands automatic equipment of knowledge research. computer studying offers those, constructing tools which could immediately observe styles in information after which use the exposed styles to foretell destiny information. This textbook bargains a accomplished and self-contained creation to the sector of computer studying, in line with a unified, probabilistic procedure. The insurance combines breadth and intensity, delivering worthwhile historical past fabric on such themes as chance, optimization, and linear algebra in addition to dialogue of modern advancements within the box, together with conditional random fields, L1 regularization, and deep studying. The e-book is written in a casual, available variety, entire with pseudo-code for crucial algorithms. All themes are copiously illustrated with colour photos and labored examples drawn from such software domain names as biology, textual content processing, desktop imaginative and prescient, and robotics. instead of offering a cookbook of other heuristic equipment, the ebook stresses a principled model-based procedure, frequently utilizing the language of graphical versions to specify types in a concise and intuitive means. just about all the versions defined were carried out in a MATLAB software program package deal -- PMTK (probabilistic modeling toolkit) -- that's freely on hand on-line. The booklet is acceptable for upper-level undergraduates with an introductory-level collage math history and starting graduate scholars.

Show sample text content

Download sample