Machine Learning • 22 lessons
From zero math to real models — complete guide.
From math prerequisites to deployment — complete Python ML with unique production pitfalls. Complete Python ML — from math prerequisites to deployment. Copyable code, run locally with pip install scikit-learn. Free, no signup.
22 lessons · Copyable code · 100% free
Preview — Python (ML)
from sklearn.linear_model import LinearRegression model = LinearRegression() model.fit(X_train, y_train) print(model.predict([[3, 1500]]))
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Curriculum
Machine Learning curriculum
Follow in order or jump to any lesson. Every lesson has a live editor.
Phase 1: Getting Started
8 lessons
First 8 lessons
01What is ML?→02ML Setup→03Python for ML→04Math for ML→05Datasets→06Supervised vs Unsupervised→07Linear Regression→08Logistic Regression→
Phase 2: Core Skills
8 lessons
Next 8 lessons
09Evaluation Metrics→10Train/Test & CV→11Trees & Forest→12SVM & k-NN→
Phase 3: Advanced
6 lessons
Final 6 lessons
17CNN→18NLP Basics→19MLOps→20House Price Project→21Image Classifier→22Ethics & Bias→