AI
AILarge Language Models (LLMs): How ChatGPT Really Works
ChatGPT feels like magic, but underneath it's a giant Transformer predicting the next token. Learn tokens, next-token prediction, pretraining, RLHF, context windows, temperature and why LLMs hallucinate — clearly.
AITransformers and Attention Explained: The Tech Behind ChatGPT
Transformers power ChatGPT, Gemini and Claude. Learn the one idea that made them possible — attention — plus why they beat RNNs, with clear diagrams, a runnable NumPy demo, and real Hugging Face code.
AIRecurrent Neural Networks (RNNs) and LSTMs Explained
CNNs handle images; RNNs handle sequences — text, speech and time series. Learn how a network gains "memory," why plain RNNs forget, and how LSTMs fix it — with diagrams and a runnable NumPy demo.
AIConvolutional Neural Networks (CNNs) Explained Simply
CNNs are the neural networks built for images. Learn how convolution, filters, ReLU and pooling let a computer "see" — with clear diagrams, a runnable NumPy demo, and real Keras code.
AIHow Neural Networks Learn: Forward Propagation, Backpropagation & Gradient Descent
A neural network starts out knowing nothing — so how does it learn? This beginner's guide explains the learning loop simply: forward propagation, loss, gradient descent, and backpropagation, with clear visuals and Python.
AILearn AI From Scratch: A Complete 38-Lesson Roadmap
A free, structured path to learn AI from absolute scratch — 38 lessons across 6 levels, from ML and neural networks to ChatGPT, RAG, agents, deployment and AI engineering, with diagrams and hands-on code. Start here.
AIWhat is a Neural Network? A Simple Visual Guide for Beginners
Neural networks power modern AI — from ChatGPT to face unlock. This beginner's guide explains what they really are: neurons, weights, and layers, with a clear diagram, a simple example, and Python you can run.
AIYour First End-to-End Machine Learning Project (Step-by-Step in Python)
Put it all together. Build your first complete machine learning project from scratch — load data, preprocess it, train a model, evaluate it, and make predictions — using the classic Titanic dataset and scikit-learn.
AIData Preprocessing in Machine Learning: Cleaning, Scaling & Encoding (Beginner's Guide)
Real-world data is messy — missing values, different scales, and text categories a model can't read. Learn the core data preprocessing steps (cleaning, handling missing data, scaling, and encoding) with simple Python examples.