ML System

Machine Learning System

This course includes

3 articles
6 mins reading time
3 videos • 32 mins

Course content

3 sections • 13 topics • Read: 6 mins • Video: 32 mins

Data Distribution Shift 5 Topics, Read: 2 mins, 1 Video: 11 mins
Distribution Shift or Data Drift
Bayes' Theorem
Covariate Shift (P(X) Changes)
Label Shift or Prior Probability Shift (P(Y) Changes)
Concept Drift or Posterior Shift (P(Y|X) Changes)
Data Distribution Shift | Covariate Shift | Label Shift | Concept Drift | Explained with Example Watch 11 mins
Retraining Strategies 4 Topics, Read: 2 mins, 1 Video: 10 mins
Why Retrain a ML Model?
Periodic Retraining (Fixed Interval)
Trigger-Based Retraining (Reactive)
Continual Learning (Online/Incremental)
Model Retraining Strategies | Periodic Retraining | Trigger- Based Retraining | Continual Learning Watch 10 mins
Deployment Patterns 4 Topics, Read: 2 mins, 1 Video: 10 mins
Deploy
Shadow Deployment
A/B Testing
Canary Deployment
Deployment Patterns in ML | Shadow Deployment | A/B Testing | Canary Deployment | Explained Watch 10 mins

Data Distribution Shift

Data Distribution Shift

Retraining Strategies

Retraining Strategies

Deployment Patterns

Deployment Patterns