عنوان

Applied machine learning /

شابک

3030181146

شابک

3030181154

شابک

3030181162

شابک

9783030181147

شابک

9783030181154

شابک

9783030181161

شابک اشتباه

3030181138

شابک اشتباه

9783030181130

عنوان اصلي

Applied machine learning /

نام عام مواد

[Book]

نام نخستين پديدآور

David Forsyth.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2019]

نام خاص و کميت اثر

1 online resource (xxi, 494 pages)

متن يادداشت

Includes bibliographical references and indexes.

متن يادداشت

I Classification -- 1 Learning to Classify -- 2 SVMs and random forests -- 3 A little learning theory -- II High dimensional data -- 4 High dimensional data -- 5 Principal component analysis -- 6 Low rank approximations -- 7 Canonical correlation analysis -- III Clustering -- 8 Clustering -- 9 Clustering using probability models -- IV Regression -- 10 Regression -- 11 Regression : choosing and managing models -- 12 Boosting -- V Graphical models -- 13 Hidden Markov models -- 14 Learning sequence models discriminatively -- 15 Mean field inference -- VI Deep networks -- 16 Simple neural networks -- 17 Simple image classifiers -- 18 Classifying images and detecting objects -- 19 Small codes for big signals.

بدون عنوان

0

متن يادداشت

Machine learning methods are now an important tool for scientists, researchers, engineers and students in a wide range of areas. This book is written for people who want to adopt and use the main tools of machine learning, but arent necessarily going to want to be machine learning researchers. Intended for students in final year undergraduate or first year graduate computer science programs in machine learning, this textbook is a machine learning toolkit. Applied Machine Learning covers many topics for people who want to use machine learning processes to get things done, with a strong emphasis on using existing tools and packages, rather than writing ones own code. A companion to the author's Probability and Statistics for Computer Science, this book picks up where the earlier book left off (but also supplies a summary of probability that the reader can use). Emphasizing the usefulness of standard machinery from applied statistics, this textbook gives an overview of the major applied areas in learning Covers the ideas in machine learning that everyone going to use learning tools should know, whatever their chosen specialty or career. Broad coverage of the area ensures enough to get the reader started, and to realize that its worth knowing more in-depth knowledge of the topic. Practical approach emphasizes using existing tools and packages quickly, with enough pragmatic material on deep networks to get the learner started without needing to study other material.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030181147

عنوان

Applied machine learning.

شماره استاندارد بين المللي کتاب و موسيقي

9783030181130

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

COM004000

موضوع مستند نشده

UYQ

موضوع مستند نشده

UYQ

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Forsyth, David

تاريخ عمليات

20200823090047.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y