🧠 Machine Learning Basics
Understand what ML is, how it works, and train real models in your browser — no install required.
Intermediate | 8 Modules | scikit-learn in Browser | ND-Friendly📌 Before You Start — Prerequisites
- Completed Introduction to Python or Python Practice Labs (or equivalent experience)
- Comfortable with variables, lists, loops, and functions in Python
- No math beyond high school algebra required — we explain the rest as we go
- A modern browser (Chrome or Firefox recommended) — no installs, no accounts
🎯 What You’ll Be Able to Do
- Explain what machine learning is (and isn’t) in plain English
- Choose the right type of ML for a given problem
- Clean and prepare data for a model
- Train and evaluate classification and regression models using scikit-learn
- Interpret results, read a confusion matrix, and understand precision vs recall
- Build a complete ML pipeline from scratch — load → clean → train → evaluate → interpret
Course Modules
What IS Machine Learning?
Rules-based vs learning-based programming. The 3 types of ML. The ML workflow from data to prediction.
Your First Dataset
What is a dataset? Rows, columns, features, labels. Exploring data and understanding what you’re working with.
Preparing Data
Cleaning messy data, encoding categories, scaling features, and splitting into train/test sets.
Your First Classifier — KNN
K-Nearest Neighbors: how distance-based classification works. Fit, predict, score with scikit-learn.
Decision Trees
How trees ask yes/no questions to classify data. Tree depth, Gini impurity, overfitting, and visualization.
Linear Regression
Predicting numbers instead of categories. Line of best fit, MSE, R² score, and when regression applies.
Evaluating Models
Why accuracy alone can mislead. Confusion matrices, precision, recall, F1-score, and when each matters.
Capstone Project
Build a complete ML pipeline. Load, explore, clean, train three models, compare results, and present your findings.
⚠ A Note on Pyodide Load Times
Each module uses Pyodide to run Python and scikit-learn directly in your browser. The first load takes about 15–20 seconds depending on your connection. After that, code runs instantly. Be patient on the first run — it’s worth it!