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ml-lifecycle

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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…

  • Updated Nov 4, 2021
  • Jupyter Notebook

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.

  • Updated May 29, 2025
  • Shell

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

  • Updated Aug 10, 2025
  • Jupyter Notebook

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