Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, Bìa mềm
Thể loại:Computers - Computer Science
Năm:2014
In lần thứ:2
Ngôn ngữ:english
Trang:457 / 452
A Proven, Hands-On Approach for Students without a Strong Statistical Foundation
Since
the best-selling first edition was published, there have been several
prominent developments in the field of machine learning, including the
increasing work on the statistical interpretations of machine learning
algorithms. Unfortunately, computer science students without a strong
statistical background often find it hard to get started in this area.
Remedying
this deficiency, Machine Learning: An Algorithmic Perspective, Second
Edition helps students understand the algorithms of machine learning. It
puts them on a path toward mastering the relevant mathematics and
statistics as well as the necessary programming and experimentation.
New to the Second Edition
Two new chapters on deep belief networks and Gaussian processes
Reorganization of the chapters to make a more natural flow of content
Revision of the support vector machine material, including a simple implementation for experiments
New
material on random forests, the perceptron convergence theorem,
accuracy methods, and conjugate gradient optimization for the
multi-layer perceptron
Additional discussions of the Kalman and particle filters
Improved code, including better use of naming conventions in Python
Suitable
for both an introductory one-semester course and more advanced courses,
the text strongly encourages students to practice with the code. Each
chapter includes detailed examples along with further reading and
problems. All of the code used to create the examples is available on
the author’s website.
