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Machine Learning for Developers

You're reading from   Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786469878
Length 270 pages
Edition 1st Edition
Languages
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Authors (2):
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Md Mahmudul Hasan Md Mahmudul Hasan
Author Profile Icon Md Mahmudul Hasan
Md Mahmudul Hasan
Rodolfo Bonnin Rodolfo Bonnin
Author Profile Icon Rodolfo Bonnin
Rodolfo Bonnin
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction - Machine Learning and Statistical Science FREE CHAPTER 2. The Learning Process 3. Clustering 4. Linear and Logistic Regression 5. Neural Networks 6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Recent Models and Developments 9. Software Installation and Configuration

Linear and Logistic Regression

After the insights we gained by grouping similar information using common features, it's time to get a bit more mathematical and start to search for a way to describe the data by using a distinct function that will condense a large amount of information, and will allow us to predict future outcomes, assuming that the data samples maintain their previous properties.

In this chapter, we will cover the following topics:

  • Linear regression with a step-by-step implementation
  • Polynomial regression
  • Logistic regression and its implementation
  • Softmax regression
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