Sentiment Analysis with Python
Sentiment Analysis involves using a machine learning model to categorize opinions expressed in text, such as tweets or chats, about a brand or product. It aims to determine whether the sentiments are positive, negative, or neutral. This analysis helps brands or product teams understand the public perception of their products, identify areas for improvement, and evaluate pricing strategies. The goal of the project mentioned is to assess the accuracy of a machine learning model in predicting sentiment (Racist or Non-Racist) based on tweets. The project utilized a dataset consisting of tens of thousands of tweets.
Content id : Tweets ID label : 1 -> denotes the tweet is racist/sexist 0 -> denotes the tweet is not racist tweet : Content of tweets
For installation of all libraries used in this project, activate your virtual environment in your command line or terminal and then run the command: py -m pip install -r requirements.txt
This project was tracked and managed with DVC(Data Version Control), so for users, a knowledge of DVC is required
* https://dvc.org/
* https://scikit-learn.org/stable/
* https://jupyter.org/