Machine Learning Algorithms (Record no. 369315)

MARC details
000 -LEADER
fixed length control field 02934 a2200241 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251208143710.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 251208b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781789347999
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bonaccorso G.
9 (RLIN) 215696
245 ## - TITLE STATEMENT
Title Machine Learning Algorithms
250 ## - EDITION STATEMENT
Edition statement 2nd Ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. Packt Publishing Ltd.
Date of publication, distribution, etc. 2018
Place of publication, distribution, etc. UK
300 ## - PHYSICAL DESCRIPTION
Extent 522p.
500 ## - GENERAL NOTE
Keywords Explore statistics and complex mathematics for data-intensive applications<br/>Discover new developments in EM algorithm, PCA, and bayesian regression<br/>Study patterns and make predictions across various datasets
520 ## - SUMMARY, ETC.
Summary, etc. Machine learning has gained tremendous popularity for its powerful and fast predictions with large datasets. However, the true forces behind its powerful output are the complex algorithms involving substantial statistical analysis that churn large datasets and generate substantial insight. This second edition of Machine Learning Algorithms walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. Once the core concepts of an algorithm have been covered, you’ll explore real-world examples based on the most diffused libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent component analysis (ICA), Bayesian regression, discriminant analysis, advanced clustering, and gaussian mixture. By the end of this book, you will have studied machine learning algorithms and be able to put them into production to make your machine learning applications more innovative.<br/>Who is this book for?<br/>Machine Learning Algorithms is for you if you are a machine learning engineer, data engineer, or junior data scientist who wants to advance in the field of predictive analytics and machine learning. Familiarity with R and Python will be an added advantage for getting the best from this book.<br/>What you will learn<br/>Study feature selection and the feature engineering process<br/>Assess performance and error trade-offs for linear regression<br/>Build a data model and understand how it works by using different types of algorithm<br/>Learn to tune the parameters of Support Vector Machines (SVM)<br/>Explore the concept of natural language processing (NLP) and recommendation systems<br/>Create a machine learning architecture from scratch
650 01 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element A Gentle Introduction to Machine Learning
9 (RLIN) 215731
650 02 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Introduction – classic and adaptive machines
9 (RLIN) 215732
650 03 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Only learning matters
9 (RLIN) 215733
650 04 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Beyond machine learning – deep learning and bio-inspired adaptive systems
9 (RLIN) 215734
650 05 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning and big data
9 (RLIN) 215735
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Vendor Cost, normal purchase price Total Checkouts Barcode Date last seen Cost, replacement price Bill Date Koha item type Original Barcode
    Dewey Decimal Classification     MCA MKSSS s K.B. Joshi Institute of Information Technology Library MKSSS s K.B. Joshi Institute of Information Technology Library 06/12/2025 8 3074.25   KBJP-BK-2887 06/12/2025 4099.00 06/12/2025 Books 2887