Software engineering, AI systems and technical paper reviews.
How I predicted California house prices with linear regression trained by gradient descent (SGDRegressor) — mutual-information feature selection, a scaling gotcha that breaks SGD, and an honest benchmark against KNN, a decision tree, and WEKA.
How I built a speech emotion recognition model in Python — parsing MFCC voice features, pruning them with mutual information, and benchmarking five classifiers (logistic regression, naïve Bayes, KNN, decision tree, MLP) in scikit-learn against WEKA.
I write about the backend×AI wedge — wins and failures included. Follow along, or say hi.