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Machine Learning

Classical ML — algorithms, math, and intuition.

InteractiveBeginner

Machine Learning Beginner

Interactive-first machine learning with scikit-learn: 284+ graded drills, 33 playgrounds, 33 lessons.

~26 hours · 41 lessons · 284+ drills · 24 quiz checkspythonmachine-learningscikit-learn
InteractiveIntermediate

Machine Learning Intermediate

Interactive-first machine learning with scikit-learn: 300+ graded drills, 35 playgrounds, 35 lessons.

~24 hours · 35 lessons · 300+ drills · 28 quiz checkspythonmachine-learningscikit-learn
InteractiveAdvanced

Machine Learning Advanced

Interactive-first machine learning with scikit-learn: 306+ graded drills, 33 playgrounds, 33 lessons.

~24 hours · 33 lessons · 306+ drills · 24 quiz checkspythonmachine-learningscikit-learn
4 ways to learnIntermediate

Machine Learning

Build real intuition for ML — play with 130+ interactive visualizations, work through guided derivations, and read the written handbook. Regression to gradient boosting and neural nets.

Concept LabGuided Deep DivesHandbook+1 more
machine-learning
InteractiveAdvanced

Advanced AI Lab

Setup required

Build AI from the ground up: backpropagation by hand in NumPy, real PyTorch on a free GPU via Colab, and an embedding model running live in your browser. Three tiers, one lab.

~6 hours · 3 lessons · 9 graded drillsadvanced-aipythonmachine-learning
3 ways to learnAdvanced

Deep Learning

How neural networks really work — interactive concepts plus guided deep dives on neural nets, transformers, CNNs, sequence models, and generative models.

Concept LabGuided Deep DivesAdvanced Labs
artificial-intelligencemachine-learning
3 ways to learnIntermediate

Math for Machine Learning

The math & statistics that ML stands on — distributions, Bayes, linear algebra, and calculus — as interactive visualizations plus a written handbook.

Concept LabHandbookAdvanced Labs
math-labsmachine-learning
InteractiveAdvanced

Machine Learning Algorithms from Scratch

Chinland InfoTech Academy flagship — build ML algorithms with NumPy only, from linear regression to decision trees, MLPs, K-Means, and PCA. 45 lessons, 360+ drills with full math derivations.

~50 hours · 45 lessons · 360 drillspythonmachine-learningnumpyfrom-scratchflagship
InteractiveIntermediate

Unsupervised Learning with Python

Core unsupervised ML with scikit-learn — K-Means, internal metrics, PCA, and real segmentation projects across 23 lessons and 184+ drills.

~25 hours · 23 lessons · 184 drillspythonmachine-learningunsupervisedscikit-learn
InteractiveAdvanced

Unsupervised Learning with Python — Advanced

Advanced unsupervised ML — hierarchical clustering, DBSCAN, GMM, spectral clustering, anomalies, text/NMF, and incremental PCA. 23 lessons, 184+ drills.

~25 hours · 23 lessons · 184 drillspythonmachine-learningunsupervisedscikit-learn