Understand AI by seeing it work.

Understand how an RNN reads a sentence word by word, with an interactive unrolled RNN. Hidden state, the RNN equation, types of RNN, backpropagation through time, vanishing and exploding gradients, NumPy and PyTorch code.

Learn how an LSTM works with an interactive, animated LSTM cell. Forget, input and output gates, the cell state, the math, a worked example, NumPy and PyTorch code, LSTM vs GRU and interview questions.

See self-attention in action. Click any word to see where it looks, then step through Q·Kᵀ, scaling, softmax and the weighted sum with real numbers. Multi-head attention, masking, positional encoding, NumPy and PyTorch code.

Learn RAG step by step with interactive visuals. Watch the RAG pipeline animate, play with chunk size and overlap, run a similarity search in your browser and see the exact prompt the LLM receives. Embeddings, vector databases, evaluation and LangChain code.

Watch an AI agent think, call tools and observe results in an animated ReAct loop. Learn what makes an agent different from a chatbot, how tool calling works, agent patterns, MCP, frameworks like LangGraph and CrewAI, and how to keep agents safe.

Step through binary search on a live array, see why O(log n) is so fast, then learn the iterative and recursive code, lower bound, first and last occurrence, binary search on the answer, common bugs and interview questions.