Blog
Learn CS and ML concepts with in-depth articles and interactive visualizations
Word2Vec Explained: How Words Become Vectors
Word2Vec turns words into meaningful vectors where similar words are close together. Learn skip-gram, CBOW, and the famous king-queen analogy with interactive examples.
Insertion Sort: Simple, Stable, and Underrated
Insertion sort builds a sorted array one element at a time — like organizing playing cards in your hand. Learn how it works, when it beats faster algorithms, and why it still matters.
LSTM Networks Explained: How AI Remembers
LSTM networks solve the vanishing gradient problem with gates that control memory. Learn how forget, input, and output gates work — with clear examples and interactive demos.
What are CNNs? Convolutional Neural Networks Explained
CNNs use filters to detect visual patterns in images — from edges to faces. Learn how convolution, feature maps, and pooling work with clear examples and interactive demos.
Activation Functions: ReLU vs Sigmoid vs Tanh
Activation functions add non-linearity to neural networks. Compare ReLU, Sigmoid, and Tanh — learn when to use each, their trade-offs, and why ReLU became the default.
Backpropagation Explained Visually
Backpropagation is how neural networks learn from mistakes. Follow gradients as they flow backward through layers, updating weights to reduce errors step by step.
What is Overfitting? (And How to Fix It)
Overfitting is when a model memorizes training data instead of learning general patterns. Learn to detect it, understand the bias-variance tradeoff, and fix it with regularization.
Merge Sort: Divide and Conquer Made Simple
Merge sort splits, sorts, and merges — delivering guaranteed O(n log n) performance every time. Learn how it works with step-by-step examples and interactive visualizations.
Binary Search Explained: Find Anything in O(log n)
Binary search finds any element in a sorted list by eliminating half the remaining options at each step. Learn how it works, when to use it, and why it's so powerful.
Quick Sort: How It Works Step by Step
Quick sort is one of the fastest sorting algorithms in practice. Learn how pivot selection and partitioning work, understand its O(n log n) average performance, and see it in action.
Bubble Sort Explained with Visualizations
Bubble sort repeatedly compares adjacent elements and swaps them if they're out of order. Learn how it works, its time complexity, and when to use it — with interactive animations.
Big O Notation: A Practical Guide for Beginners
Big O notation describes how an algorithm's performance scales with input size. Learn O(1), O(n), O(log n), O(n log n), and O(n²) with clear examples and comparisons.
What is an Algorithm? The Complete Beginner's Guide
An algorithm is a step-by-step procedure for solving a problem. Learn what algorithms are, why they matter, and explore common examples from sorting to searching.
What is a Neural Network? Explained Simply
Neural networks are the foundation of modern AI. Learn how layers of simple math operations combine to recognize images, understand language, and make predictions.
What is Machine Learning? A Visual Introduction
Machine learning lets computers learn from data instead of following explicit rules. Learn the core concepts, types of ML, and see how neural networks actually learn — with interactive visualizations.