Sentiment-Analysis-Model-Training

Sentiment Analysis Model Training

View note book here: https://sidney-hc.github.io/Sentiment-Analysis-Model-Training/

Introduction

This project aims to perform sentiment analysis on a combination of three datasets: the Sentiment 140 dataset, IMDB movie review dataset, and a subset of the Amazon review dataset. The goal is to accurately classify text data into positive and negative sentiments using advanced machine learning techniques and hyperparameter optimization.

Datasets

1. Sentiment 140 Dataset: Contains 1.6 million tweets labeled as positive or negative.
2. IMDB Movie Review Dataset: Comprises 50,000 movie reviews, equally split between positive and negative sentiments.
3. Amazon Review Subset: A subset consisting of 3.6 million product reviews, categorized into positive and negative sentiments.

Installation

Prerequisites

• Python 3.7+
• pip

Install Required Packages

Clone the repository:

git clone https://github.com/yourusername/sentiment-analysis.git
cd sentiment-analysis