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MLKB

1 · Overview

1.1 Introduction
1.2 ML Project Lifecycle
1.3 ML Project Checklist
1.4 MLOps
1.5 Case Study: Speech Recognition System

2 · Design

2.1 Scoping
2.2 Data

3 · Development

3.1 Modeling Overview
3.2 Validation and Hyperparameter Tuning
3.3 Model Baseline
3.4 Error Analysis
3.5 Prioritizing Improvements
3.6 Skewed Datasets
3.7 Performance Auditing
3.8 Data-centric AI Development
3.9 Experiment Tracking

4 · Deployment

4.1 Key Challenges in Deployment
4.2 Deployment Architecture
4.3 Common Deployment Patterns
4.4 Reproducibility and CI/CD
4.5 Monitoring
4.6 Case Study: Defect Inspection in Manufacturing

Appendix

Templates
Sources

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© Copyright 2026, Tomás Ravalli.

Rules of Machine Learning by Martin Zinkevich is paraphrased under CC BY 4.0.