A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀

Track experiments, log metrics, manage models — MLflow from Julia.

A curated list of awesome open source and commercial platforms for serving models in production 🚀

A curated list of awesome open source and commercial MLOps platforms 🚀

Connecting MLJ and MLFlow

In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype…

This project integrates Hyperledger Fabric with machine learning to enhance transparency and trust in data-driven workflows. It outlines a blockchain-based strategy for data traceability, model auditability, and secure ML deployment across consortium networks.

A controlled environment to play around with various data errors and stages in the ML lifecycle and measure their impact on model fairness and stability.

Predict the future sale price of a bulldozer, given its characteristics and previous examples of how much similar bulldozers have been sold for...

I walk you though what an entire machine learning cycle looks like for a binary classification problem. For this walkthrough, we are utilizing UCI's Iranian Churn dataset

A complete machine learning internship repository covering Python basics, data preprocessing, EDA, model training, serialization, and a Streamlit spam classifier demo for real-time predictions.

AI Product Management portfolio (Duke AI PM program): MVP & lifecycle design, build-vs-buy economics, medical-image-annotation capstone, bias & fairness audits, MLOps orchestration. Python · Jupyter.

Machine learning experiment tracking and model management using MLflow