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ML & AI Tools
Explore AI-powered tools and platforms
MLflow
Track and manage ML experiments
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Coming SoonAbout MLflow
MLflow is a platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. This instance is hosted for community use and experimentation.
Features
- Track experiments and parameters
- Compare model performance
- Manage model versions
- Deploy models to production
Disclaimer
This MLflow server is a personal project and has no affiliation with Databricks or the official MLflow project. It is maintained independently for educational and experimental purposes.
Personal Project Notice
This service is not affiliated with my professional work and is maintained as a hobby project. Use at your own discretion. For production deployments, please refer to the official MLflow documentation and consider enterprise solutions.
YouTube Playlists
Check out my playlists
Articles & Guides
Technical articles and documentation
Learning a language is easy, discover how.
Introduction Have you ever been amazed by people who are able to speak more than one language? They know how to convey ideas and express themselves in different situations, regardless of the language...
The Detective's Toolkit: Alibi for Drift Detection.
As a data scientist, you have been working on a model for several weeks, and the metrics you defined as success criteria now look promising. Learn about drift detection in production environments...
Make the most out of your Jupyter Notebooks using Poetry.
Exploratory Data Analysis (EDA) is the first stage of any data science project. Discover how to manage your Jupyter Notebook dependencies with Poetry for better reproducibility...