Advanced data science and analytics with python (Record no. 30936)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230110b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781138315068
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number ROG
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Rogel-Salazar, Jesus
245 ## - TITLE STATEMENT
Title Advanced data science and analytics with python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc CRC Press,
Date of publication, distribution, etc 2020
Place of publication, distribution, etc Boca Raton :
300 ## - PHYSICAL DESCRIPTION
Extent xxxv, 383 p. ;
Other physical details ill.,
Dimensions 24 cm
365 ## - TRADE PRICE
Price amount 48.99
Price type code GBP
Unit of pricing 104.60
490 ## - SERIES STATEMENT
Series statement Chapman & Hall/CRC data mining & knowledge discovery series
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Database Management
Topical term or geographic name as entry element Data mining
Topical term or geographic name as entry element Exploration de donnees
Topical term or geographic name as entry element Programming and Design
Topical term or geographic name as entry element Computer program language
Topical term or geographic name as entry element Computer Graphics
Topical term or geographic name as entry element Activation function
Topical term or geographic name as entry element Bayes' theorem
Topical term or geographic name as entry element Chain rule
Topical term or geographic name as entry element Backpropogation
Topical term or geographic name as entry element LSTM
Topical term or geographic name as entry element Hidden layer
Topical term or geographic name as entry element Pandas
Topical term or geographic name as entry element Social network analysis
Topical term or geographic name as entry element Natural language processing
Topical term or geographic name as entry element Neural network
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Checked out Date last seen Date last borrowed Koha item type
          DAIICT DAIICT 2023-01-10 5124.35 1 006.312 ROG 033404 2024-07-15 2024-07-01 2024-07-01 Books

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