Math & Computer Science

Convolution kernels explained. Learn edge detection for images using filters and the Sobel operator. Essential computer vision concepts with Python.

Unlock the math behind 22/7! Learn how continued fractions generate increasingly accurate rational approximations for irrational numbers like pi

Explore the math behind language. Learn how formal grammars shape speech, code, NLP, and the rules machines use to understand us.

Master set theory: definitions, notation, set operations (union, intersection), and common sets. Essential concepts for higher mathematics.

Perlin noise for procedural generation. Learn to create realistic mountains, cliffs, and caves with parameters like persistence, lacunarity, and Fractal Brownian Motion.

Explore the Gale-Shapley Algorithm and the Stable Matching Problem. Learn how algorithms create stable pairings, not just perfect matches.

Learn how to find an Eulerian Path using Graph Theory and the degree of a vertex. Discover the solution to the Bridges of Königsberg puzzle.

Discover Turing’s Turochamp, Learn about Alan Turing’s foundational paper-and-pencil chess algorithm and the birth of AI in games.

Explore prime number math: shortcuts, primality tests, Mersenne numbers, and the Lucas-Lehmer Test for finding the largest primes.

Explore the Fibonacci sequence, Golden Ratio (φ), and their appearance in nature, from flowers to the staircase problem in math.

Explore Hilbert’s Hotel Paradox and transfinite numbers. Learn how to accommodate infinite guests, buses, and spaceships using infinity math.

Learn the Tower of Hanoi Proof using Proof by Induction. Discover the minimum moves required for this classic combinatorics puzzle.

Essential tips for math degree survival at university. Master notation, proofs, and the shift from high school to degree-level mathematics.

Part 3 of building a Python Chess Engine. Implement the move function for game simulation, encode move types, and filter out illegal moves.

Python chess engine development. Use bitboards and bitwise operations for efficient move generation for sliding and non-sliding pieces.

Learn K-Means Clustering for Image Segmentation in Python. Achieve color reduction and optimized performance using NumPy

Maximize chess engine speed with Python Bitboards. Use 1-Hot Encoding and bitwise operations to create an efficient board data structure.

Solve the Travelling Salesman Problem with a Genetic Algorithm. Learn selection, crossover, and mutation steps to find a near-optimal route.

The TSP is NP-Hard due to exponential complexity. Understand the time-accuracy trade-off in finding optimal vs. approximate routes.

The Genetic Algorithm uses Darwinian Evolution for machine learning. Learn selection, crossover, and mutation for efficient optimization.