Learn AI Series (#24) - Dimensionality Reduction - PCA What will I learn You will learn the curse of dimensionality -- why more features isn't always better, and how high-dimensional spaces break your

Learn AI Series (#23) - Advanced Clustering - Beyond K-Means What will I learn You will learn DBSCAN -- density-based clustering that finds arbitrarily shaped clusters and identifies noise points

Learn Creative Coding (#22) - Mini-Project: Audio Visualizer Phase 3 finale. We've learned easing, state machines, physics, audio analysis, recording, and shaders. Time to smash the best parts together

Learn AI Series (#22) - K-Means Clustering - Finding Groups What will I learn You will learn unsupervised learning -- discovering structure in data without any labels at all; the K-Means algorithm from

Learn AI Series (#21) - Mini Project - Predicting Crypto Market Regimes What will I learn You will learn how to apply everything from episodes #1-20 to a real, messy, end-to-end classification problem;

Learn Creative Coding (#21) - Shaders: A First Taste of GLSL Everything we've built so far in this series runs on the CPU. Every pixel we've drawn, every particle we've simulated, every noise value we've

Learn AI Series (#20) - Support Vector Machines - Drawing the Perfect Boundary What will I learn You will learn the maximum margin principle -- why SVMs seek the widest possible gap between classes, and

En esta entrega continuamos avanzando con entusiasmo en el estudio de la Geometría Analítica, explorando ahora los ejercicios del Grupo 16 del clásico texto de Lehmann. En esta nueva entrega nos adentramos

¡Hemos llegado al gran final del nivel avanzado y de toda la serie! En esta quinta entrega encontrarás los últimos ejercicios resueltos paso a paso, completando así un recorrido de 25 ejercicios para este

¡Seguimos avanzando! En esta segunda entrega del nivel intermedio, te traigo otros ejercicios para que continúes fortaleciendo tus habilidades en el manejo de las Ecuaciones Diferenciales Exactas. ¡Comencemos!

Learn AI Series (#19) - Gradient Boosting - The Kaggle Champion What will I learn You will learn the difference between bagging and boosting -- two fundamentally different ensemble strategies that start

Learn Creative Coding (#20) - Recording and Exporting: GIF, PNG Sequence, Video You've built some beautiful things over the last ten episodes. A particle galaxy that reacts to your mouse. Physics simulations

Learn AI Series (#18) - Random Forests - Wisdom of Crowds What will I learn You will learn why combining many weak models creates a strong one -- the ensemble principle and the math that makes it work;

Learn AI Series (#17) - Decision Trees - How Machines Make Decisions What will I learn You will learn how decision trees split data by asking yes/no questions about features -- a radically different approach

Learn Creative Coding (#19) - Sound-Reactive Visuals Last episode we gave our particles mass. Springs that overshoot and settle, friction that makes things slide, flocking boids that self-organize into

Learn AI Series (#16) - Scikit-Learn - The Standard Library of ML What will I learn You will learn why scikit-learn became the standard ML library and how its API design makes everything we built from

Learn AI Series (#15) - Feature Engineering and Selection What will I learn You will learn how to create new features from raw data that help your model find patterns it couldn't see before; interaction

Learn Creative Coding (#18) - Physics Lite: Springs, Friction, and Flocking Last episode we gave our sketches memory with state machines -- different modes, transitions between them, timeline sequencing.

Learn AI Series (#14) - Data Preparation - The 80% Nobody Talks About What will I learn You will learn the three-way split (train/validation/test) and why two sets are not enough for serious ML work; the

Learn AI Series (#13) - Evaluation - How to Know If Your Model Actually Works What will I learn You will learn why accuracy alone is a terrible metric for most real-world problems; the confusion matrix