Book Image

Machine Learning for Emotion Analysis in Python

By : Allan Ramsay, Tariq Ahmad
5 (1)
Book Image

Machine Learning for Emotion Analysis in Python

5 (1)
By: Allan Ramsay, Tariq Ahmad

Overview of this book

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.
Table of Contents (18 chapters)
1
Part 1:Essentials
3
Part 2:Building and Using a Dataset
7
Part 3:Approaches
14
Part 4:Case Study

Non-English datasets

Often, finding a dataset to train your model is the most challenging part of the project. There may be occasions where a dataset is available but it is in a different language—this is where translation can be used to make that dataset useful for your task. There are a number of different ways to translate a dataset, as listed here:

  • Ask someone you know, who knows the language
  • Employ a specialist translation company
  • Use an online translation service (e.g. Google Translate) either through the GUI or via an API

Clearly, the first two are the preferred options; however, they come with an associated cost in terms of effort, time, and money. The third option is also a good option, especially if there is a lot of data that needs translating. However, this option should be used with care because (as we will see) translation services have nuances, and each can produce different results.

There are lots of different translation services available...