Introduction to Machine Learning Deployment
Chapter 1: Getting Started with Model Deployment
What is Machine Learning Deployment?
Why Deploy Machine Learning Models?
The Machine Learning Workflow Overview
Types of Deployment Strategies (Introduction)
Challenges in Model Deployment
Quiz for Chapter 1
Chapter 2: Preparing Your Model for Deployment
Saving Trained Models
Introduction to Model Serialization
Using Pickle for Model Persistence
Using Joblib for Model Persistence
Handling Model Dependencies
Saving Preprocessing Steps
Hands-on Practical: Saving and Loading a Simple Model
Quiz for Chapter 2
Chapter 3: Creating a Prediction Service with Flask
What is an API?
Introduction to Web Frameworks
Setting Up Flask
Creating a Basic Flask Application
Loading Your Saved Model in Flask
Defining a Prediction Endpoint
Handling Input Data (JSON)
Returning Predictions
Testing Your API Locally
Hands-on Practical: Building a Simple Flask Prediction API
Quiz for Chapter 3
Chapter 4: Introduction to Containerization with Docker
What is Containerization?
Introduction to Docker
Docker Concepts: Images and Containers
Installing Docker
Writing a Simple Dockerfile
Building a Docker Image for the Flask App
Running the Application in a Docker Container
Hands-on Practical: Containerizing the Prediction Service
Quiz for Chapter 4
Using Pickle for Model Persistence
Was this section helpful?
pickle- Python object serialization, Python core developers, 2024 - Provides comprehensive documentation for Python'spicklemodule, detailing its functions, usage, and important security considerations for serialization and deserialization.- Persistence model, Scikit-learn developers, 2024 - Outlines methods for saving and loading scikit-learn models, including practical examples using
picklefor model persistence. - Designing Machine Learning Systems: New Ways of Thinking in Product Development, Chip Huyen, 2022 (O'Reilly Media) - A highly regarded book on building and deploying machine learning systems, providing context on the role of model persistence within a larger ML deployment pipeline.
© 2025 ApX Machine LearningEngineered with