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R Machine Learning By Example

You're reading from   R Machine Learning By Example Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784390846
Length 340 pages
Edition 1st Edition
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Author (1):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with R and Machine Learning FREE CHAPTER 2. Let's Help Machines Learn 3. Predicting Customer Shopping Trends with Market Basket Analysis 4. Building a Product Recommendation System 5. Credit Risk Detection and Prediction – Descriptive Analytics 6. Credit Risk Detection and Prediction – Predictive Analytics 7. Social Media Analysis – Analyzing Twitter Data 8. Sentiment Analysis of Twitter Data Index

Getting started with Twitter APIs


Twitter is as much a delight for tweeple (people using Twitter to tweet) as it is for data scientists. The APIs and the documentation are well updated and easy to use. Let us get started with the APIs.

Overview

Twitter has one of easiest yet most powerful set of APIs available of any social network out there. These APIs have been used by Twitter itself and data scientists to understand the dynamics of the Twitter world. Twitter APIs make use of four different objects, namely:

  • Tweets: A tweet is the central entity that defines Twitter itself. As discussed in the previous section, a tweet contains far more information (metadata) than just the content/message of the tweet.

  • Users: Anybody or anything that can tweet, follow, or perform any of Twitter's actions is a user. Twitter is unique in its definition of user, which need not necessarily be a human. @MarsCuriosity is one such nonhuman popular Twitter handle with over 2 million followers!

  • Entities: These are structured...

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