Machine Learning – A Probabilistic Perspective - Image 1

£78.86

MIT Press Machine Learning – A Probabilistic Perspective

Name: Machine Learning - A Probabilistic Perspective
Brand: MIT Press
Price: 78.86 GBP
Availability: InStock

Multicolor

E-business

This is the usual price. Wait for it to drop, or tell us your number.

£79 today · usual range £0–£0 · best ever £45

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 595 days • 595 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 595 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £71-79 (534 days, 89.7%)

Price range: £45 - £88

Price levels: 5 price ranges over 595 days

Description

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package―PMTK (probabilistic modeling toolkit)―that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Key Features

New Store Stock

Product Specifications

Brand: MIT Press
Colour: Multicolor
Format: Hardcover
ASIN: 0262018020
Category: Books > Subjects > Business, Finance & Law > E-Commerce > E-business
Domain: Amazon UK
Release Date: 18 September 2012
Listed Since: 09 February 2012

Barcode

No barcode data available

MIT Press Machine Learning – A Probabilistic Perspective

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Key Features

Product Specifications

Barcode

Similar Products You Might Like

Mathematics and Programming for Machine Learning with R: From the Ground Up

Model-Based Machine Learning

Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning

The Hundred-Page Machine Learning Book

Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver Data Mining

Machine Learning and Artificial Intelligence

Machine Learning: A Guide to Current Research: 12 (The Springer International Series in Engineering and Computer Science, 12)

Applied Machine Learning Using mlr3 in R

Machine Learning and its Applications

Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R

A Practical Machine Learning with R: Tutorials and Case Studies

Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner

Machine Learning: Theory and Practice

Machine Learning: A Guide to Current Research: 12 (The Springer International Series in Engineering and Computer Science, 12)

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

An Elementary Introduction to Statistical Learning Theory (Wiley Series in Probability and Statistics)

Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems: 1

Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems: 1

Fundamental Mathematical Concepts for Machine Learning in Science

Applied Machine Learning

Machine Learning: From the Classics to Deep Networks, Transformers, and Diffusion Models