Convexity, Logistic Loss, and the Overfitting Battle
Why squared error fails for classification, implementing Binary Cross-Entropy, and fighting high variance with regularization.
May 12, 20266 min read
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Machine Learning
Documenting my journey to master Machine Learning. The focus is on consistent practice: writing code, training models, and daily improvement. Expect detailed project notes and a transparent look at what it takes to learn ML from scratch.
Logistic Regression and Decision Surfaces
Why standard regression fails at classification and how the Sigmoid function fixes the probability space.
Feb 3, 20265 min read
Optimization Mechanics — Feature Scaling, Convergence Testing, and Polynomial Mapping
Eliminating gradient descent bottlenecks through input normalization and feature engineering.
Jan 21, 20266 min read
Upgrading to Multiple Linear Regression
Moving past single-variable equations and smashing matrix dot products into NumPy to accelerate training.
Jan 18, 20265 min read
gradient_descent.py
Translating the calculus of partial derivatives into simultaneous parameter updates using raw NumPy.
Jan 15, 20265 min read
Cost function in linear regression
Dissecting the Squared Error Cost Function in Linear Regression
Jan 12, 20264 min read