Welcome to the "Emotion Detection from Text" machine learning program! This Python program is designed to analyze and determine the emotion conveyed in a given text using natural language processing techniques and machine learning.
The main objective of this program is to help users check the emotion expressed in a piece of text. By utilizing machine learning and natural language processing, the program classifies the input text into different emotions such as happy, sad, angry, surprised, and more.
The repository contains the following files:
- python.py - Python script for emotion detection from text.
- requirements.txt - A list of required Python packages to run the program.
- text.txt - Sample text file used for testing the emotion detection.
To get started with the emotion detection program, follow these steps:
- Clone the repository locally using
git clone [repository_url]. - Install the required Python packages by running
pip install -r requirements.txt. - Ensure you have Python and the necessary libraries installed (specified in
requirements.txt). - Run the
python.pyscript and input the text you want to analyze for emotion. - The program will predict and display the detected emotion for the given text.
The program utilizes a machine learning model trained on a labeled dataset to predict emotions in the text. It's important to note that the accuracy of the emotion detection may vary based on the complexity and context of the input text. Experiment with different texts to observe the model's performance.
This project is licensed under the MIT License, allowing you to freely use, modify, and distribute the codebase under the terms specified in the license.
Feel free to explore the repository and try out the emotion detection capabilities of this machine learning program!
Please note: The accuracy of emotion detection depends on the training data and the model used. You may consider fine-tuning the model or training it on a larger and more diverse dataset to improve performance for specific use cases.