Introduction to MLOps
Chapter 1: Foundations of MLOps
What is MLOps?
Why MLOps is Necessary for Machine Learning
MLOps vs. DevOps: Similarities and Differences
The Goals of an MLOps Strategy
Core Principles of MLOps
Common Challenges in Production Machine Learning
Chapter 2: The Machine Learning Lifecycle
Overview of the End-to-End ML Lifecycle
Data Ingestion and Preparation
Model Training and Experimentation
Model Evaluation and Validation
Model Deployment Strategies
Monitoring Models in Production
The Feedback Loop for Model Improvement
Chapter 3: Versioning in Machine Learning
The Importance of Reproducibility
Version Control for Code with Git
Introduction to Data Versioning
Techniques for Model Versioning
Managing Experiment Tracking
Hands-on Practical: Versioning a Simple ML Project
Chapter 4: Automation and CI/CD for ML
Introduction to CI/CD
Continuous Integration (CI) for ML Code
Continuous Delivery (CD) for Models
Continuous Training (CT)
Building a Basic ML Pipeline
Introduction to Orchestration Tools
Hands-on Practical: Create a Simple CI Pipeline with GitHub Actions
Chapter 5: Model Deployment and Serving
What is Model Deployment?
Containerization with Docker
Creating a Model API with Flask
Deployment Patterns: Online vs. Batch Prediction
Introduction to Model Registries
Fundamentals of Model Monitoring
Hands-on Practical: Package and Deploy a Model as a Docker Container
Introduction to Orchestration Tools
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- Building Machine Learning Pipelines, Hannes Hapke, Catherine Nelson, and Rahul Agarwal, 2020 (O'Reilly Media) - Provides practical guidance on building, deploying, and maintaining ML pipelines, including the necessity and patterns of orchestration.
- Apache Airflow Documentation, The Apache Software Foundation, 2024 - Official documentation for Apache Airflow, detailing its architecture, DAG definitions, and operational aspects for workflow orchestration.
- Kubeflow Pipelines Documentation, The Kubeflow Authors, 2024 - Official documentation for Kubeflow Pipelines, outlining its Kubernetes-native design for building and managing ML workflows.
- About GitHub Actions, GitHub Docs, 2022 (GitHub, Inc.) - Official documentation introducing GitHub Actions for automating software development workflows, including CI/CD and event-driven tasks.