How Machines Learn

An interactive journey through the fundamentals of machine learning

01

Pattern Discovery & Learning

Find the hidden pattern and learn how machines discover weights

02

Applications & Loss Functions

From real-world predictions to choosing the right error measure

03

Classification: Making Decisions

From predicting numbers to predicting yes/no answers

04

Vectors & Deep Learning

From points to vectors: the foundation of modern AI

05

Matrices: The Building Blocks

From numbers to vectors to matrices—the foundation of neural networks

06

Embeddings: Words to Numbers

How AI captures the meaning of language

Coming Soon
07

Non-Linearity: Why Stacking Layers Matters

Activation functions, deep learning, and how neural networks learn complex patterns

Coming Soon
08

Attention: How Models Know What Matters

Understanding the mechanism that revolutionized AI and powers modern transformers

Coming Soon
09

Modern LLM Architectures

Test-time compute, MoE, reasoning models, and the latest breakthroughs

Coming Soon
10

RAG: Building AI That Knows Your Data

From theory to production: Retrieval-Augmented Generation explained and deployed

Start Your Journey

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