Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	September 2015
Genre:	EDV / Informatik
	Analytics / Big Data / clustering disciminative approach / COMPUTERS / Data Science / Machine Learning / data statistics / generative approach / Hypothesis testing / Learning Models / least-squares / machine learning / multi-dimensional probability distributions / multi-task learning outlier detection / probability / Statistical pattern recognition mehr...
ISBN:	9780128021217
EAN-Code:	9780128021217
Verlag:	Elsevier
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 191 mm / D 27 mm
Gewicht:	1110 gr
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials. . Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks.