Shayne Biagi

Housing Price Forecasting with the Help of Random Forests

code

machine learning

regression

Housing prices vary significantly year after year and continue to do so throughout multiple generations. Housing prices are notoriously hard to understand. Being affected by…

Harnessing Probability Theory: Naive Bayes for Classification

code

machine learning

probability theory

statistics

Probability theory is a branch of mathematics which works to quantify uncertainty and randomness, providing us with a formal framework for expressing and manipulating…

Exploring Ceramic Composition with K-Means Clustering

code

machine learning

clustering

Spanning centuries of craftsmanship and art, the world of ceramics provides us with unique insights into artisans of…

Multi-Class Classification with a Single-Layer Perceptron Model

code

machine learning

classification

neural networks

In Machine Learning, learning and implementing classification models are a fundamental step on any data scientist’s journey. Here in…

Unveiling Malicious Software with Anomaly Detection

code

machine learning

clustering

cybersecurity

In the ever-changing field of cybersecurity, the persistent challenge of malware detection continues to demand more sophisticated approaches day by day. Today, we…

Synthetic Data Generation with Variational Autoencoders

generative ai

code

machine learning

neural networks

In the modern age of big data, robust and diverse datasets are extremely valuable. Data is what fuels the machine learning models that we, as a society, rely on for much of…

Ethics of Intelligent Government Surveillance Systems

ethics

machine learning

data analytics

Predictive policing and social credit systems have been gaining attention due to their potential to enhance public safety and security. However, the implementation of such…

Pierre Sarabamoun, Shaunak Juvekar, Shayne Biagi, Shrikanth Upadhayaya, Srujan Vithalani

Deep Learning Equity Trading Model

machine learning

data analytics

neural networks

This project seeks to rely on recent deep learning and technical analysis advancements to generate predictions of short term price movements for the Apple stock, $AAPL.

Shayne Biagi, Andrew Istfan, Franco Medrano

Analysis of A Push-Relabel Based Additive Approximation for Optimal Transport

optimal transport

transport theory

machine learning

mathematics

algorithms

Optimal transport is quite expensive to compute exactly, so there have been recent desires for fast and reliable approximation algorithms. Here I analyze and describe a…

Analysis of A Graph Theoretic Additive Approximation of Optimal Transport

optimal transport

transport theory

machine learning

mathematics

algorithms

In this post, I describe and analyze a graph theoretic additive approximation algorithm for approximating Optimal Transport.…

Hypothetical Applications of Optimal Transport

optimal transport

transport theory

Here, I discuss some possible hypothetical applications of the Optimal Transport algorithms.

What is the Optimal Transport Problem?

optimal transport

transport theory

mathematics

statistics

First, let us begin with a…

Pandoc Guide

code

documentation

This is a detailed, topic-based guide to Pandoc aimed at students in Creating User Documentation (ENGL3814) at Virginia Tech.

Mason Gelletly, Lucy Paul, Shayne Biagi, Ashlyn East, Theodore Gunn