divagora / Machine-Learning-Projects

A collection of short machine learning projects.

Machine Learning Portfolio

This repository contains a collection of various machine learning projects completed over the last two years.

Contents

Regression

• Gaussian Process Regression. This project considers the use of a Gaussian process to model and predict monthly atmospheric carbon dioxide concentration.

Clustering

• K-Means Clustering. This project explores the use of a Gaussian mixture model and the k-means algorithm to obtain an automatic segmentation of an image, and to automatically count the number of cells in the image.

Dimensionality Reduction

• Principal Components Analysis. This project investigates the use of dimensionality reduction via principal component analysis (PCA) within a classification algorithm for face recognition

Deep Learning

• Recurrent Neural Networks. This project investigates the use of recurrent neural networks to predict the price of two popular cryptocurrencies.
• Convolutional Neural Networks. This project explores the use of a convolutional neural network to classify images.
• Generative Adversarial Networks. This project considers the use of a generatie adversarial network (GAN) to generate new images of faces.

Natural Language Processing

• Text Classification. This project applies several standard techniques (including naive Bayes, logistic regression, support vector machines (SVMs), and deep neural networks) - to perform text classification.