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Advanced Data Science and Analytics with Python / Jesús Rogel-Salazar.

By: Material type: TextTextSeries: Chapman & Hall/CRC data mining & knowledge discovery seriesPublisher: Boca Raton : CRC Press, 2020Description: 383 pages : illustrations ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781138315068
  • 9780429446610
Subject(s): DDC classification:
  • 006.312 21 R.J. A 2020
LOC classification:
  • QA76.9.D343 .R637 2020
Summary: "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"--
List(s) this item appears in: Computer Science 2020-2021
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Holdings
Item type Current library Call number Status Date due Barcode
Books Books Main Library Main Stacks 006.312 R.J. A 2020 (Browse shelf(Opens below)) Available 00018709
Browsing Main Library shelves, Shelving location: Main Stacks Close shelf browser (Hides shelf browser)
006.31 Z.A. F 2018 Feature Engineering for Machine Learning : 006.312 C.B. S 2018 Spark : 006.312 K.V. D 2018 Data Science : 006.312 R.J. A 2020 Advanced Data Science and Analytics with Python / 006.312 S.G. B 2020 Big data analytics / 006.32 A.C. N 2018 Neural Networks and Deep Learning : 006.32 C.R. E 1999 The essence of neural networks /

Includes bibliographical references and index.

"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"--

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