Course 1/4 : Introduction to Machine Learning in Production (MLOps) , Coursera Notes

Course 1 Introduction to Machine Learning in Production: Week 1

Code Link : Github Repo

Reading Material Week 1:

• Machine Learning in Production: Why You Should Care About Data and Concept Drift
• Monitoring Machine Learning Models in Production
• A Chat with Andrew on MLOps: From Model-centric to Data-centric AI

Week 2

Code Link : Google Colab

Refernce :

1. 3 — Baselines
2. Responsible Machine Learning with Error Analysis
3. Want to track and compare all your ML experiments with zero extra work?
4. Start tracking in 5 mins (or less via integration).
5. Track first experiments
   ML Experiment Tracking: What It Is, Why It Matters, and How to Implement It

Week 3

Resource:

1. https://cs230.stanford.edu/blog/datapipeline/#best-practices
2. https://csgaobb.github.io/Projects/DLDL.html
3. https://blog.tensorflow.org/2021/01/ml-metadata-version-control-for-ml.html
4. https://cloud.google.com/blog/products/ai-machine-learning/key-requirements-for-an-mlops-foundation