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Introduction to Reliable ML
Who Should Take This Course?
Why Do We Need Tests?
Various Software Testing Paradigms
Example: Microservice Lacking Tests
Quiz: Introduction to Reliable ML
Software Testing
Unit Testing
Introduction to pytest
Fixtures in pytest
Integration Testing
Mocks and Patches
Mutation and Property-Based Tests
Quiz: Software Testing
Best and Worst Practices
Test-Driven Development
Flaky and Negative Tests
Automation of Testing
Quiz: Best and Worst Practices
ML-Specific Tests
Why Machine Learning is Specific
Behavioral Testing
Comparing the Environments
Tests for Exact Values
Smoke Tests for the ML Pipeline
Fixtures and Mocks in Machine Learning Tests
Samples as Tests
Quiz: ML-Specific Tests
ML Software Reliability outside of Tests
Runtime Checks
Type Hinting
Logging and Debugging
ML Monitoring Guide
Quiz: ML Software Reliability Outside of Tests
Wrapping Up
Conclusion
Appendix
Advanced pytest Features
Links for Additional Reading
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Reliable Machine Learning
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Read and watch additional info on reliable machine learning.
We'll cover the following...
Software testing
Best and worst practices
Test-driven development
Code coverage
CI/CD
ML software readability
Runtime checks
Type hinting
Logging and debugging
Monitoring
Software testing
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pytest official documentation
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