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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

Introducing the problem statement


At the beginning of the chapter, we already looked at an overview of the problem statement. Here, we will be delving into further details. We want to build an automatic text summarization application. We will be providing a medical transcription document as the input. Our goal is to generate the summary of this document. Note that here, we are going to provide a single document as the input, and as an output, we will be generating the summary of that single document. We want to generate an informative summary for the document. An informative summary is a type of summary where the summarization document is a substitute of the original document as far as the converging of information is concerned. This is because we are dealing with the medical domain.

Initially, we use extractive summarization methods in our approaches. We will be generating the extractive summary for a medical document. Later on in this chapter, we will be also developing a solution that...

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