albincorreya/ml-training-airflow-mlflow-example

An example of setting up local audio ML training pipeline on Airflow with MLFlow experiment tracking and custom python library.

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This project provides an example of setting up a local machine learning operations (MLOps) pipeline for audio classification tasks. It takes raw audio data and configurations as input, processes it through a defined workflow, and outputs trained machine learning models along with tracked experiment results. This is ideal for data scientists who want to learn how to integrate open-source tools for managing ML training workflows.

No commits in the last 6 months.

Use this if you are a data scientist looking to understand and implement a local MLOps pipeline using open-source tools like Airflow and MLFlow for audio ML training.

Not ideal if you are looking for a production-ready cloud-based MLOps solution or a simple library for immediate use without infrastructure setup.

audio-classification machine-learning-operations data-science-workflow experiment-tracking ML-training
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 17 / 25

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9

Language

Python

License

Last pushed

Nov 18, 2022

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