A showcase of my work, categorized by project type
Pipeline to predict heart disease by tuning classical classifiers with a Genetic Algorithm (via NIAPY & PSO) and then refining deep-learning model architectures using AutoKeras neural-architecture search.
Applies PCA to the scikit-learn breast cancer dataset to reduce feature dimensionality and visualize principal component structure.
Combines fuzzy-c-means feature generation with a neural-network classifier to predict diabetes outcomes on the Pima Indians dataset.
A pipeline to classify breast tumors (malignant vs. benign) using a Decision Tree model on clinical feature data.
A regression pipeline to predict used-car prices based on vehicle attributes, using linear models and visual diagnostics.
Uses a Multinomial Naïve Bayes model to predict passengers’ embarkation port from key demographic and fare features.
A text-classification pipeline that uses TF-IDF features and a Multinomial Naïve Bayes classifier to predict the language of input sentences.
Loads and inspects an Excel dataset, then reads and parses a text file to extract specific customer names and monetary values using regular expressions.
A pipeline that classifies handwritten digit images (MNIST) using PCA for dimensionality reduction and supervised classifiers (Decision Tree, SVM).
A step-by-step walkthrough of basic supervised learning workflows using the Iris dataset.
With my academic excellence and practical experience in IT, web development, and data analysis, I offer specialized consultation and development services for graduation projects across various fields.