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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example The easiest way to get into machine learning

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781783553112
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Ivan Idris Ivan Idris
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Ivan Idris
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Table of Contents (9) Chapters Close

Preface 1. Getting Started with Python and Machine Learning 2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms FREE CHAPTER 3. Spam Email Detection with Naive Bayes 4. News Topic Classification with Support Vector Machine 5. Click-Through Prediction with Tree-Based Algorithms 6. Click-Through Prediction with Logistic Regression 7. Stock Price Prediction with Regression Algorithms 8. Best Practices

What is NLP?

The 20 newsgroup dataset is composed of text, taken from news articles as its name implies. It was originally collected by Ken Lang, and is now widely used for experiments in text applications of machine learning techniques, specifically natural language processing techniques.

Natural language processing (NLP) is a significant subfield of machine learning, which deals with the interactions between machine (computer) and human (natural) languages. Natural languages are not limited to speech and conversation. They can be in writing and sign languages as well. The data for NLP tasks can be in different forms, for example, text from social media posts, web pages, even medical prescription, audio from voice mail, commands to control systems, even a favorite music or movie. Nowadays, NLP has been broadly involved in our daily lives: we can not live without machine translation; weather forecast scripts are...

You have been reading a chapter from
Python Machine Learning By Example
Published in: May 2017
Publisher: Packt
ISBN-13: 9781783553112
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