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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Chapter 5. Sentiment Analysis

So far, we have explored some really cool applications in the analytics domain. In this chapter, we will explore the famous Natural Language Processing (NLP) technique, which you may have already guessed because of the name of the chapter. Absolutely right; we will build a sentiment analysis-based application. In general, everyone is familiar with sentiment analysis-based applications. If you aren't, then don't worry. We will discuss and understand all the necessary details.

First of all, I want to give you a basic idea about sentiment analysis. I will provide an example so it will be easy for you to understand. Regardless of where we live, we all watch movies. Nowadays, we read reviews or others' opinions on various social media platforms. After that, if a majority of the opinions about the movie are good, then we watch that movie. If the opinions are not impressive, we might not watch the movie. So during this entire process, our mind analyzes these opinions...

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