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F# for Machine Learning Essentials

ebook

Get up and running with machine learning with F# in a fun and functional way

About This Book

  • Design algorithms in F# to tackle complex computing problems
  • Be a proficient F# data scientist using this simple-to-follow guide
  • Solve real-world, data-related problems with robust statistical models, built for a range of datasets

    Who This Book Is For

    If you are a C# or an F# developer who now wants to explore the area of machine learning, then this book is for you. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.

    What You Will Learn

  • Use F# to find patterns through raw data
  • Build a set of classification systems using Accord.NET, Weka, and F#
  • Run machine learning jobs on the Cloud with MBrace
  • Perform mathematical operations on matrices and vectors using Math.NET
  • Use a recommender system for your own problem domain
  • Identify tourist spots across the globe using inputs from the user with decision tree algorithms

    In Detail

    The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs.

    If you want to learn how to use F# to build machine learning systems, then this is the book you want.

    Starting with an introduction to the several categories on machine learning, you will quickly learn to implement time-tested, supervised learning algorithms. You will gradually move on to solving problems on predicting housing pricing using Regression Analysis. You will then learn to use Accord.NET to implement SVM techniques and clustering. You will also learn to build a recommender system for your e-commerce site from scratch. Finally, you will dive into advanced topics such as implementing neural network algorithms while performing sentiment analysis on your data.

    Style and approach

    This book is a fast-paced tutorial guide that uses hands-on examples to explain real-world applications of machine learning. Using practical examples, the book will explore several machine learning techniques and also describe how you can use F# to build machine learning systems.


  • Expand title description text
    Publisher: Packt Publishing

    Kindle Book

    • Release date: February 25, 2016

    OverDrive Read

    • ISBN: 9781783989355
    • File size: 17024 KB
    • Release date: February 25, 2016

    EPUB ebook

    • ISBN: 9781783989355
    • File size: 17024 KB
    • Release date: February 25, 2016

    PDF ebook

    • ISBN: 9781783989355
    • File size: 21303 KB
    • Release date: February 25, 2016

    Formats

    Kindle Book
    OverDrive Read
    EPUB ebook
    PDF ebook

    Languages

    English

    Get up and running with machine learning with F# in a fun and functional way

    About This Book

  • Design algorithms in F# to tackle complex computing problems
  • Be a proficient F# data scientist using this simple-to-follow guide
  • Solve real-world, data-related problems with robust statistical models, built for a range of datasets

    Who This Book Is For

    If you are a C# or an F# developer who now wants to explore the area of machine learning, then this book is for you. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.

    What You Will Learn

  • Use F# to find patterns through raw data
  • Build a set of classification systems using Accord.NET, Weka, and F#
  • Run machine learning jobs on the Cloud with MBrace
  • Perform mathematical operations on matrices and vectors using Math.NET
  • Use a recommender system for your own problem domain
  • Identify tourist spots across the globe using inputs from the user with decision tree algorithms

    In Detail

    The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs.

    If you want to learn how to use F# to build machine learning systems, then this is the book you want.

    Starting with an introduction to the several categories on machine learning, you will quickly learn to implement time-tested, supervised learning algorithms. You will gradually move on to solving problems on predicting housing pricing using Regression Analysis. You will then learn to use Accord.NET to implement SVM techniques and clustering. You will also learn to build a recommender system for your e-commerce site from scratch. Finally, you will dive into advanced topics such as implementing neural network algorithms while performing sentiment analysis on your data.

    Style and approach

    This book is a fast-paced tutorial guide that uses hands-on examples to explain real-world applications of machine learning. Using practical examples, the book will explore several machine learning techniques and also describe how you can use F# to build machine learning systems.


  • Expand title description text
    • Details

      Publisher:
      Packt Publishing

      Kindle Book
      Release date: February 25, 2016

      OverDrive Read
      ISBN: 9781783989355
      File size: 17024 KB
      Release date: February 25, 2016

      EPUB ebook
      ISBN: 9781783989355
      File size: 17024 KB
      Release date: February 25, 2016

      PDF ebook
      ISBN: 9781783989355
      File size: 21303 KB
      Release date: February 25, 2016

    • Creators
    • Formats
      Kindle Book
      OverDrive Read
      EPUB ebook
      PDF ebook
    • Languages
      English