Aashu Aggarwal·Jun 3Neural Networks — An Attempt at ThinkingFrom pixels to a prediction — how neural networks learn to think
Aashu Aggarwal·Apr 5Logistic Regression: Drawing the Line Between Yes and NoUsing gradient descent and the sigmoid function to classify data into categories
Aashu Aggarwal·Feb 25A Prompt Engineering Application — Building a Study Planner for My DaughterBuilding a spaced repetition study planner with prompt engineering and LLMs
Aashu Aggarwal·Feb 15Linear Regression: Where Math Meets DataFinding the best-fit line through data using gradient descent
Aashu Aggarwal·Feb 2Gradient Descent: Walking Downhill to Find the BottomHow machine learning models learn by following gradients step-by-step to minimize loss and optimize performance.
Aashu Aggarwal·Jan 17Optimization with Derivatives: Finding the Peak (and the Valley)How gradients find optimal points, why some aren’t what they seem, and what this means for training AI models.
Aashu Aggarwal·Jan 7The Gradient: Your Compass in High-Dimensional SpaceFrom single variables to thousands of parameters: How gradients guide machine learning through complex landscapes.
Aashu Aggarwal·Dec 18, 2025The Derivative: Mathematics’ Way of Measuring ChangeHow measuring change powers AI: From your phone’s GPS to ChatGPT, derivatives make it all work.
Aashu Aggarwal·Nov 22, 2025Why Casinos Always Win: Understanding the Law of Large NumbersCan you predict what millions will do by asking just a thousand? LLN and CLT are here to help.A response icon1A response icon1
Aashu Aggarwal·Nov 1, 2025From Sceptic to Believer: Updating Our Beliefs with Bayes’ TheoremWatch your beliefs evolve rationally as evidence accumulates — the mathematics of updating certainty
