Jithsaavvy/Sentiment-analysis-from-MLOps-paradigm
This project promulgates an automated end-to-end ML pipeline that trains a biLSTM network for sentiment analysis, experiment tracking, benchmarking by model testing and evaluation, model transitioning to production followed by deployment into cloud instance via CI/CD
This project provides an automated system for analyzing the sentiment of text, such as social media posts. It takes raw text data, processes it, trains a deep learning model to understand sentiment, and then makes that model available for real-time use. It's designed for data scientists or machine learning engineers who need to build and manage robust sentiment analysis systems.
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Use this if you need an automated, end-to-end solution for training, evaluating, and deploying a sentiment analysis model, especially for production environments requiring continuous integration and deployment.
Not ideal if you are looking for a simple, off-the-shelf sentiment analysis tool without needing to manage the underlying machine learning operations.
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15
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Language
Python
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Last pushed
Feb 01, 2023
Commits (30d)
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