Introduction

Welcome to the wonderful world of machine learning!

What is Machine Learning?

Machine learning is a type of artificial intelligence (AI) that allows computers to learn from data without being explicitly programmed. Think about how you learn. You learn from experience. If you see a few dogs, you start to understand what a dog looks like. If you touch a hot stove, you learn to not do it again.

Machine learning works in a similar way. We feed a computer a lot of data (like pictures of dogs) and it learns to recognize patterns in that data. The more data it sees, the better it gets at its task.

Why learn about machine learning?

Machine learning is all around us! It’s the technology that powers:

  • Recommendation engines: When Netflix suggests a movie you might like, or when Amazon recommends a product, that’s machine learning at work.
  • Spam filters: Your email service uses machine learning to figure out which emails are junk and which are important.
  • Voice assistants: When you talk to Siri, Alexa, or Google Assistant, they use machine learning to understand what you’re saying.
  • Self-driving cars: These cars use machine learning to understand their surroundings and make decisions.

By learning about machine learning, you’ll have a better understanding of the technology that is shaping our world. You’ll also be able to build your own amazing things!

Where we’re headed

In this course, we’ll start with the basics and build our way up. Here’s a quick look at what we’ll cover:

  • Lesson 1: Definitions: We’ll learn the basic vocabulary of machine learning.
  • Lesson 2: Categories of ML: We’ll explore the different types of machine learning.
  • Lesson 3: The ML Process: We’ll learn about the steps involved in building a machine learning model.
  • Lessons 4-8: Building Models: We’ll get our hands dirty and build our own machine learning models using Python. We’ll cover Linear Regression, Logistic Regression, Naive Bayes, K-Nearest Neighbors, and K-Means Clustering.

By the end of this course, you’ll have a solid foundation in machine learning and you’ll be ready to start exploring this exciting field on your own.

Course structure

The course is broken up into topic with each page focusing on a single area of machine learning.

Requirements

A Google account is required to create your own Google Colab notebook.