Fun with Learning Technology

Learn Courses Questions Tracks Tools News Explore Practice

Fun with Learning Technology

A new problem, explained clearly, every day.

Learn

Lessons
Topics
News
Tools
Courses
Career tracks
Everything

Site

About
Contact
Support
Privacy
Terms

Get the daily one

One email per new problem. No spam.

Request a tutorial

Requests shape what gets made next.

© 2026 Fun with Learning TechnologyRSS

Machine Learning — Free Course — Fun with Learning Technology

Home›Courses›Machine Learning

🤖

Machine Learning

ML algorithms, evaluation, and real-world workflows

35 topics7 sections35 lessons ready

01

Fundamentals

6

ML Overview — Supervised, Unsupervised, Reinforcement
Train / Validation / Test Split
Bias-Variance Tradeoff
Cross-Validation
Feature Engineering and Selection
Handling Imbalanced Data

02

Supervised Learning

8

Linear Regression
Logistic Regression
Decision Trees
Random Forests
Gradient Boosting — XGBoost, LightGBM
Support Vector Machines (SVM)
K-Nearest Neighbors (KNN)
Naive Bayes

03

Unsupervised Learning

5

K-Means Clustering
Hierarchical Clustering
DBSCAN
Dimensionality Reduction — PCA
t-SNE and UMAP

04

Evaluation

4

Classification Metrics — Accuracy, Precision, Recall, F1
ROC Curve and AUC-ROC
Regression Metrics — MAE, RMSE, R²
Confusion Matrix

05

Model Workflow

5

Scikit-learn Pipeline
Hyperparameter Tuning — GridSearch, RandomSearch, Optuna
Model Serialization — pickle and joblib
Handling Missing Data in ML
Feature Scaling — StandardScaler, MinMaxScaler

06

Model Training Deep Dive

4

Stochastic Gradient Descent
Learning Rate and Schedulers
Regularization — L1 (Lasso) and L2 (Ridge)
Early Stopping

07

Interview Prep

3

ML Interview Questions — Algorithms
ML Interview Questions — Math and Stats
ML System Design Questions

Start learning Machine Learning

Free to read. Sign in to save progress, take quizzes and keep notes.

Open the course