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Data Science  with Python

You're reading from   Data Science with Python Combine Python with machine learning principles to discover hidden patterns in raw data

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Product type Paperback
Published in Jul 2019
Publisher Packt
ISBN-13 9781838552862
Length 426 pages
Edition 1st Edition
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Authors (3):
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Rohan Chopra Rohan Chopra
Author Profile Icon Rohan Chopra
Rohan Chopra
Mohamed Noordeen Alaudeen Mohamed Noordeen Alaudeen
Author Profile Icon Mohamed Noordeen Alaudeen
Mohamed Noordeen Alaudeen
Aaron England Aaron England
Author Profile Icon Aaron England
Aaron England
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Toc

Table of Contents (10) Chapters Close

About the Book 1. Introduction to Data Science and Data Pre-Processing FREE CHAPTER 2. Data Visualization 3. Introduction to Machine Learning via Scikit-Learn 4. Dimensionality Reduction and Unsupervised Learning 5. Mastering Structured Data 6. Decoding Images 7. Processing Human Language 8. Tips and Tricks of the Trade 1. Appendix

Introduction

One of the most important goals of artificial intelligence (AI) is to understand the human language to perform tasks. Spellcheck, sentiment analysis, question answering, chat bots, and virtual assistants (such as Siri and Google Assistant) all have a natural language processing (NLP) module. The NLP module enables virtual assistants to process human language and perform actions based on it. For example, when we say, "OK Google, set an alarm for 7 A.M.", the speech is first converted to text and then this text is processed by the NLP module. After this processing, the virtual assistant calls the appropriate API of the Alarm/Clock application. Processing human language has its own set of challenges because it is ambiguous, with words meaning different things depending on the context in which they are used. This is the biggest pain point of language for AI.

Another big reason is the unavailability of complete information. We tend to leave out most of the information while...

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