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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

Handling Model Dependencies

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References

venv - Creation of virtual environments, Python Software Foundation, 2023 - Official guide to creating and managing isolated Python environments, which is essential for dependency consistency across projects.
pip User Guide: Requirements Files, The pip developers, 2023 - Documentation describing how to use requirements.txt files to declare and install project dependencies, which supports reproducible environments.
Model persistence, scikit-learn developers, 2023 - Official guide on saving and loading scikit-learn models, emphasizing the necessity of matching library versions for proper functionality and avoiding issues.
Managing environments, Anaconda Documentation Team, 2023 - Guide on creating, activating, and managing conda environments for different projects, including specifying Python versions and dependencies.

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