Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

Artificial intelligence and machine learning are the technologies of the future, and this is the perfect time to tap into their potential and add value to your business. Machine Learning for Emotion Analysis in Python helps you employ these cutting-edge technologies in your customer feedback system and in turn grow your business exponentially.

With this book, you’ll take your foundational data science skills and grow them in the exciting realm of emotion analysis. By following a practical approach, you’ll turn customer feedback into meaningful insights assisting you in making smart and data-driven business decisions.

The book will help you understand how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you’re set up for success, you’ll explore complex ML techniques, uncovering the concepts of deep neural networks, support vector machines, conditional probabilities, and more. Finally, you’ll acquire practical knowledge using in-depth use cases showing how the experimental results can be transformed into real-life examples and how emotion mining can help track short- and long-term changes in public opinion.

By the end of this book, you’ll be well-equipped to use emotion mining and analysis to drive business decisions.

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Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

Artificial intelligence and machine learning are the technologies of the future, and this is the perfect time to tap into their potential and add value to your business. Machine Learning for Emotion Analysis in Python helps you employ these cutting-edge technologies in your customer feedback system and in turn grow your business exponentially.

With this book, you’ll take your foundational data science skills and grow them in the exciting realm of emotion analysis. By following a practical approach, you’ll turn customer feedback into meaningful insights assisting you in making smart and data-driven business decisions.

The book will help you understand how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you’re set up for success, you’ll explore complex ML techniques, uncovering the concepts of deep neural networks, support vector machines, conditional probabilities, and more. Finally, you’ll acquire practical knowledge using in-depth use cases showing how the experimental results can be transformed into real-life examples and how emotion mining can help track short- and long-term changes in public opinion.

By the end of this book, you’ll be well-equipped to use emotion mining and analysis to drive business decisions.

39.99 In Stock
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning

eBook

$39.99 

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Overview

Artificial intelligence and machine learning are the technologies of the future, and this is the perfect time to tap into their potential and add value to your business. Machine Learning for Emotion Analysis in Python helps you employ these cutting-edge technologies in your customer feedback system and in turn grow your business exponentially.

With this book, you’ll take your foundational data science skills and grow them in the exciting realm of emotion analysis. By following a practical approach, you’ll turn customer feedback into meaningful insights assisting you in making smart and data-driven business decisions.

The book will help you understand how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you’re set up for success, you’ll explore complex ML techniques, uncovering the concepts of deep neural networks, support vector machines, conditional probabilities, and more. Finally, you’ll acquire practical knowledge using in-depth use cases showing how the experimental results can be transformed into real-life examples and how emotion mining can help track short- and long-term changes in public opinion.

By the end of this book, you’ll be well-equipped to use emotion mining and analysis to drive business decisions.


Product Details

ISBN-13: 9781803246710
Publisher: Packt Publishing
Publication date: 09/28/2023
Sold by: Barnes & Noble
Format: eBook
Pages: 334
File size: 9 MB

About the Author

Allan Ramsay is an Emeritus Professor. He is highly skilled in Python and has extensive knowledge of Emotion Analysis.
Dr. Tariq Ahmad is an experienced Data Scientist with a demonstrated history of working in the I.T. industry. He is highly skilled in Python, C#, MVC, SQL Server. He has Ph.D. in Emotion Analysis.

Table of Contents

Table of Contents
  1. Foundations
  2. Building and Using a Dataset
  3. Labelling Data
  4. Preprocessing - Stemming, Tagging, and Parsing
  5. Sentiment Lexicons and Vector-Space Models
  6. Naïve Bayes
  7. Support Vector Machines
  8. Neural Networks and Deep Neural Networks
  9. Exploring Transformers
  10. Multiclassifiers
  11. Case Study - The Qatar Blockade
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