Supervised and Unsupervised Learning for Data Science Book [PDF] Download

Download the fantastic book titled Supervised and Unsupervised Learning for Data Science written by Michael W. Berry, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Supervised and Unsupervised Learning for Data Science", which was released on 04 September 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.

Summary of Supervised and Unsupervised Learning for Data Science by Michael W. Berry PDF

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.


Detail About Supervised and Unsupervised Learning for Data Science PDF

  • Author : Michael W. Berry
  • Publisher : Springer Nature
  • Genre : Technology & Engineering
  • Total Pages : 191 pages
  • ISBN : 3030224759
  • PDF File Size : 36,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Supervised and Unsupervised Learning for Data Science

Supervised and Unsupervised Learning for Data Science
  • Publisher : Springer Nature
  • File Size : 24,7 Mb
  • Release Date : 04 September 2019
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This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data

Machine Learning and Data Science Blueprints for Finance

Machine Learning and Data Science Blueprints for Finance
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 43,6 Mb
  • Release Date : 01 October 2020
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Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine

Machine Learning

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  • Publisher : BPB Publications
  • File Size : 25,9 Mb
  • Release Date : 16 September 2021
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Concepts of Machine Learning with Practical Approaches. KEY FEATURES ● Includes real-scenario examples to explain the working of Machine Learning algorithms. ● Includes graphical and statistical representation to simplify modeling Machine Learning

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  • Publisher : CRC Press
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  • Release Date : 20 November 2019
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  • Publisher : Packt Publishing Ltd
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  • Release Date : 21 July 2017
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Build Machine Learning models with a sound statistical understanding. About This Book Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. Implement statistical computations programmatically

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  • Publisher : John Wiley & Sons
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  • Release Date : 09 February 2021
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One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you

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  • Publisher : Vinaitheerthan Renganathan
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  • Release Date : 02 June 2021
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Machine Learning models are widely used in different fields such as Artificial Intelligence, Business, Clinical and Biological Sciences which includes self-driving cars, predictive models, disease prediction, genome sequencing, spam filtering,

Hands-On Unsupervised Learning Using Python

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  • Publisher : O'Reilly Media
  • File Size : 40,7 Mb
  • Release Date : 21 February 2019
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Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is

Hands-on Supervised Learning with Python

Hands-on Supervised Learning with Python
  • Publisher : BPB Publications
  • File Size : 39,9 Mb
  • Release Date : 06 January 2021
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Hands-On ML problem solving and creating solutions using Python KEY FEATURES _Introduction to Python Programming _Python for Machine Learning _Introduction to Machine Learning _Introduction to Predictive Modelling, Supervised and Unsupervised