Machine Learning with Python for Everyone. (Record no. 61492)

MARC details
000 -LEADER
fixed length control field 02309nam a22002417a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240404104309.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789353944902
028 ## - DISTRIBUTOR NAME
Distributor Name : Donated by Pearson
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.133 FEN
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Fenner, Mark E.
245 ## - TITLE STATEMENT
Title Machine Learning with Python for Everyone.
Statement of responsibility, etc / Mark E Fenner.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc , Noida
Name of publisher, distributor, etc : Pearson India
Date of publication, distribution, etc ,2023.
300 ## - PHYSICAL DESCRIPTION
Extent xxvi,473p.
Dimensions : 26cm.
365 ## - TRADE PRICE
Price amount 00
505 ## - FORMATTED CONTENTS NOTE
Contents note Chapter 1: Let’s discuss learning Chapter 2: predicting categories: getting started with classification Chapter 3: predicting numerical values: getting started with regression Chapter 4: evaluating and comparing learners Chapter 5: evaluating classifiers Chapter 6: evaluating Regressors Chapter 7: more classification methods Chapter 8: more regression methods Chapter 9: manual feature engineering: manipulating data for fun and Profit Chapter 10: models that engineer features for us Chapter 11: feature engineering for domains: domain-specific learning online chapters Chapter 12: tuning hyperparameters and pipelines Chapter 13: combining learners Chapter 14: connecting, extensions, and further directions
520 ## - SUMMARY, ETC.
Summary, etc Students are crushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine learning with Python for everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently. Reflecting 20 years of experience teaching non-specialists, the author teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, the book presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical “code-alongs,” and easy-to-understand images -- focusing on Mathematics only where it’s necessary to make connection and deepen insight.
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 Python
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Addison Wesley Data & Analytics Series
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Mark E Fenner.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 04/04/2024 Donated by Pearson India 0.00 5 4 005.133 FEN G3504 01/12/2025 17/10/2025 04/04/2024 Books
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