Learning Sentiment Analysis in Python

Overview

This repository is designed to facilitate the learning of sentiment analysis using Python. It provides a rich blend of theoretical background and practical examples to understand how sentiment analysis works. Through this repository, learners can grasp how to process textual data, apply natural language processing (NLP) techniques, and utilize machine learning algorithms to analyze and determine the sentiment expressed in texts.

Features

• Theoretical Explanations: Understand the core concepts behind sentiment analysis, including how sentiments are defined and measured.

• Practical Coding Examples: Dive into Python code examples that demonstrate real-world applications of sentiment analysis.

• Step-by-Step Tutorials: Follow detailed tutorials to build your sentiment analysis projects from scratch.

• Resources and References: Access a curated list of additional resources for deeper learning and exploration.

Getting Started

To get started with this repository:

1. Clone the repository:

   git clone https://github.com/Naviden/Sentiment-Analysis-in-Python.git
   

2. Explore the tutorials and code examples available in the repository to begin your learning journey.

Prerequisites

• Basic understanding of Python programming
• Familiarity with basic machine learning concepts is beneficial but not required

Contents

• tutorials/: Step-by-step guides to learn sentiment analysis
• examples/: Practical Python code examples demonstrating sentiment analysis applications
• docs/: Additional documentation and resources for deeper understanding