Artificial Intelligence (AI) is a branch of computer science that focuses on building systems capable of performing tasks that normally require human intelligence — such as learning, reasoning, problem-solving, perception, and language understanding.

An online book introduction to machine learning

Textbook for IND5003 course

This repository contains implementations of various machine learning algorithms focused on predictive analysis. It serves as a resource for learning and experimenting with predictive modeling techniques using R.

Jupyter notebook with demonstration of PCA on a high-dimensional genomic data set.

Machine Learning for Network Engineers

Customer segmentation analysis using unsupervised learning on German demographics data (Bertelsmann Arvato Analytics). The project applies data preprocessing, PCA for dimensionality reduction, and KMeans clustering to identify customer groups that are over-represented compared to the general population.

Part II: Unsupervised machine learning in R to cluster and identify candidate countries for international expansion, using PCA, K-Means, and DBSCAN.

An unsupervised approach to music recommendation without accessing other users' data and use traditional recommendation algorithms like collaborative filtering.

Developed for "Management and Analysis of Physics Dataset Mod. B," this project uses Dask and CloudVeneto VMs to handle a massive 250GB dataset. Clustering on 800k RCV1 articles involves dataset reduction by macrocategory and also implementing cosine similarity for improved clustering, as suggested by Natural Language Processing principles.

Personal collection of machine learning methods and utilities built for fast, reusable implementation. It covers core steps like preprocessing, modeling, tuning, and evaluation — with compact code and embedded explanations to streamline real-world ML workflows.

Built an unsupervised Machine Learning pipeline to detect anomalies in Bitcoin transactions by selecting 19 key features from 700.

Unsupervised Learning: Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Welcome to my Portfolio!

This repository contains coursework and implementations for the Clustering and Dimensionality Reduction class, part of the Honours Bachelor of Artificial Intelligence degree at Durham College.

Social distancing from clean code: the Jessops approach to Data Mining.

A study for a UK bank, undertaking segmentation analysis to identify trends and patterns in their customers.

NLP-based workforce analytics using TF-IDF, clustering, and career trajectory analysis from LinkedIn data.

This project is part of Introduction to Machine Learning with PyTorch Nanodegree by Udacity