AI Lab Methods & Projects

Lab-based AI projects covering ANN classification, Naive Bayes spam detection, time-series forecasting, and statistical data preprocessing.

Source on GitHub

Sunspot data as two lagged inputs against the output: most points sit near zero, a few cycles reach 150 and above.Open full size: Sunspot data as two lagged inputs

A collection of lab exercises that walks through the AI toolkit end-to-end: ANN classification on tabular data, Naive Bayes for spam detection, classical time-series forecasting, and the statistical preprocessing steps that make everything downstream work.

Figures

Sunspot forecast against the true series: the timing is right, but it overshoots most peaks.Open full size: Sunspot forecast against the true series

Spam and ham counts for the ten most frequent words. Markup tokens like 3D, font and br lean strongly toward spam.Open full size: Spam and ham counts for the

Five clusters on the Fresh and Grocery features, centers marked. One holds just four outliers.Open full size: Five clusters on the Fresh and

Average silhouette score for 2 to 9 clusters on the Fresh and Frozen features. Two clusters score best, at about 0.62.Open full size: Average silhouette score for 2 to

Correspondence

Research, data science work or a question about a project. Email, LinkedIn or the contact form all reach me.

mawangot2000@gmail.com LinkedIn

There is also a contact form, and aresume (PDF).