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F# for Machine Learning Essentials

You're reading from   F# for Machine Learning Essentials Get up and running with machine learning with F# in a fun and functional way

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781783989348
Length 194 pages
Edition 1st Edition
Languages
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Author (1):
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Sudipta Mukherjee Sudipta Mukherjee
Author Profile Icon Sudipta Mukherjee
Sudipta Mukherjee
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Toc

Table of Contents (9) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 2. Linear Regression 3. Classification Techniques 4. Information Retrieval 5. Collaborative Filtering 6. Sentiment Analysis 7. Anomaly Detection Index

Machine learning frameworks

I will be using the following machine learning frameworks to solve some of the real problems throughout the book:

You are much better off using these frameworks than creating your own because a lot of work has been done and they are used in the industry. So if you pick up using these frameworks along the way while learning about machine learning algorithms in general, that's a great thing. You will be in luck.

You have been reading a chapter from
F# for Machine Learning Essentials
Published in: Feb 2016
Publisher:
ISBN-13: 9781783989348
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