This project is an end-to-end MLOps platform designed to classify machine learning projects using a Large Language Model (BERT). It demonstrates the complete lifecycle of an AI application, from processing raw text data and performing distributed training and hyperparameter tuning to evaluating performance and serving the trained model via a scalable web API.
Made-With-ML is organized as connected concepts and components. Start broad, then drill down chapter by chapter.
This project is an end-to-end MLOps platform designed to classify machine learning projects using a Large Language Model (BERT). It demonstrates the complete lifecycle of an AI application, from processing raw text data and performing distributed training and hyperparameter tuning to evaluating performance and serving the trained model via a scalable web API.
Source Repository: https://github.com/GokuMohandas/Made-With-ML
Follow sequentially or jump to any topic. Start with Data Processing Pipeline.
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