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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

Quiz
Beta

Chapter: Introduction to Containerization with Docker

Test your understanding and practice the concepts from this chapter

Quiz Instructions

This quiz contains 14 questions to help you practice.
You need to score at least 70% to pass.
Attempts: Unlimited.
Your highest score will be kept.
Please attempt this quiz without assistance; however, feel free to refer to the chapter notes or use a code interpreter if needed.
This assessment is for your learning and understanding, It is not formally accredited (yet).

Question Format

The questions are designed to be engaging, focusing on understanding, application, and interpretation rather than rote memorization. Expect scenario-based problems that test your ability to apply what you've learned.

Attempts

Best scores and quiz attempts will appear.

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