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008 200508s2020 flu ob 001 0 eng
040 _aOCoLC-P
_beng
_erda
_cOCoLC-P
020 _a9780429446641 (electronic bk)
020 _a0429446640 (electronic bk)
020 _a9780429822308
_q(electronic bk. : Mobipocket)
020 _a0429822308
_q(electronic bk. : Mobipocket)
020 _a9780429822315
_q(electronic bk. : EPUB)
020 _a0429822316
_q(electronic bk. : EPUB)
020 _z9781138315068
020 _z1138315060
020 _z9780429446610
020 _z0429446616
020 _a9780429822322
_q(electronic bk.)
020 _a0429822324
_q(electronic bk.)
035 _a(OCoLC)1154070455
_z(OCoLC)1155202754
_z(OCoLC)1155638026
035 _a(OCoLC-P)1154070455
050 4 _aQA76.9.D343
_bR637 2020
072 7 _aBUS
_x061000
_2bisacsh
072 7 _aCOM
_x012040
_2bisacsh
072 7 _aCOM
_x021030
_2bisacsh
072 7 _aUN
_2bicssc
082 0 4 _a006.3/12
_223
100 1 _aRogel-Salazar, Jesus,
_eauthor.
245 1 0 _aAdvanced data science and analytics with Python /
_cJesús Rogel-Salazar.
264 1 _aBoca Raton :
_bCRC Press,
_c2020.
300 _a1 online resource (1 volume :
_billustrations (black and white.).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aChapman & Hall/CRC data mining & knowledge discovery series
520 _a"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"--
505 0 _a1.No Time To Lose: Time Series Analysis2.Speaking Naturally: Text and Natural Language Processing3.Let Us Get Social: Graph Theory and Social Network Analysis4.Thinking Deeply: Neural Networks and Deep Learning5.Here Is One I Made Earlier: Machine Learning Deployment
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aData mining.
650 0 _aPython (Computer program language)
650 0 _aDatabases.
650 7 _aBUSINESS & ECONOMICS / Statistics
_2bisacsh
650 7 _aCOMPUTERS / Computer Graphics / Game Programming & Design
_2bisacsh
650 7 _aCOMPUTERS / Database Management / Data Mining
_2bisacsh
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9780429446641
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c5589
_d5589