Polytech-Machine-Learning-Projects

Ensemble of machine learning projects from Polytech.

Projects:

1 - Sleep Phase Classification

This project aims to classify which part of sleep the person is in through their brain activity information.

It uses and compare the following classification algorithmns: Gaussian Naive Bayesian, Linear Discriminant Analysis, and Quadratic Discriminant Analysis.

2 - Classification of natural and artificial images, and classification of image subject.

This project aims to classify images as natural or artificial, as well as their classes (for example, if the image is of a forest, a city, and so on).

It uses and compares the classification algorithms: SVM, MLP, CNN, and a transfer learning method with fine-tuning, using VGG16.

(To run, the images need to be unzipped in their folder.)"

3 - Diagnostic of coronary disease in patients

This project aims to detect whether the patient has coronary disease using data from blood analysis, electrocardiograms, and the physical characteristics of the patient.

4 - Classification of whether a tumor is cancerous using an unsupervised method

This project aims to determine whether a tumor is cancerous using data from a sample taken from the patient's tumor. The extracted characteristics of the sample are already available in the dataset for this task. The K-means algorithm is used as the clustering method to address this problem.