Machine Learning: Master Supervised & Unsupervised Learning Algorithms With Real Examples (Record no. 43257)

MARC details
000 -LEADER
fixed length control field 01835nam a2200229Ia 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230309s9999 xx 000 0 und d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789391392352
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31 DOS
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Doshi, Ruchi
245 ## - TITLE STATEMENT
Title Machine Learning: Master Supervised & Unsupervised Learning Algorithms With Real Examples
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Bpb Publications
Place of publication, distribution, etc New Delhi
Date of publication, distribution, etc 2022
300 ## - PHYSICAL DESCRIPTION
Extent 270
520 ## - SUMMARY, ETC.
Summary, etc The book offers the readers the fundamental concepts of Machine Learning techniques in a user-friendly language. The book aims to give in-depth knowledge of the different Machine Learning (ML) algorithms and the practical implementation of the various ML approaches. This book covers different Supervised Machine Learning algorithms such as Linear Regression Model, Naïve Bayes classifier Decision Tree, K-nearest neighbor, Logistic Regression, Support Vector Machine, Random forest algorithms, Unsupervised Machine Learning algorithms such as k-means clustering, Hierarchical Clustering, Probabilistic clustering, Association rule mining, Apriori Algorithm, f-p growth algorithm, Gaussian mixture model and Reinforcement Learning algorithm such as Markov Decision Process (MDP), Bellman equations, policy evaluation using Monte Carlo, Policy iteration and Value iteration, Q-Learning, State-Action-Reward-State-Action (SARSA). It also includes various feature extraction and feature selection techniques, the Recommender System, and a brief overview of Deep Learning.By the end of this book, the reader can understand Machine Learning concepts and easily implement various ML algorithms to real-world problems.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Science
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Vector Machine
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Hiran, Kamal Kant
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Jain, Ritesh Kumar
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book

No items available.