Technologies Used
Python
NLP
BiLSTM
GloVe
Machine Learning
SVM
TF-IDF
Project Overview
Built Part-of-Speech tagging models using both traditional ML (Logistic Regression, SVM) and deep learning (BiLSTM) approaches. The BiLSTM model with GloVe embeddings achieved 94.78% accuracy, significantly outperforming traditional methods.
Key Features
- Implemented using Python, NLP, BiLSTM
- Developed during Oct 2023 - Dec 2023
- Focused on performance, usability, and modern design principles
- Utilized best practices for code organization and maintainability
Development Process
This project was developed with a focus on creating a robust and scalable solution. The development process involved careful planning, implementation of key features, rigorous testing, and deployment.
Project Details
Related Skills
PythonNLPBiLSTMGloVeMachine LearningSVM