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adv_r_course_lab3

lab 3

advr_lab5

apply_sklearn

Apply some of the main machine learning algorithms with sklearn library in different data sets, also did some visualization to explore the data. All the exercises are from Pierian Data.

bookstore_mini_project

A GUI with which you can stores and manipulate book titles in a database. Libraries used: Tkinter and SQLite.

chemformer

cnn_interpretability

This project is about detecting pneumonia or no pneumonia from x-ray images and trying to explain the predictions of the Network.

dnn_with_keras

Finding the right hyperparameteres for a Deep Neural Network with keras. Classification task with 7 classes. Use cartographic variables to classify forest categories.

fastbook

The fastai book, published as Jupyter Notebooks

information_theory_s_relation_to_machine_learning

A theoretical approach of the relation between Information Theory and Machine Learning.

lmridger

mnist_classification

Classification of the famous dataset of Mnist, applying the Support Vector Machine algorithm and a Radial Basis Function Network. These assignments were for the course Neural Networks from Aristotle University of Thessaloníki. February 2017.

nlp-multilabel-classification

The scope of this project is to apply a number of tools on solving a machine learning problem. The NLP Multilabel classification problem is chosen.

pca_kmeans_matlab

An assignment in which dimension reduction is applied with PCA, clustering with k-means algorithm and classification with Naive Bayes Classifier. Implemented in MATLAB, using the MNIST dataset.

pytorch-mini-projects

Apply different Neural Network architectures in Pytorch.

text_classification_on_imdb_reviews

A sentiment analysis task of classifying the polarity (positive or negative) of IMDb reviews. Using 'traditional' machine learning.

utilizing-nlp-transfer-learning-with-ulmfit-in-chemoinformatics

This project was carried out as a part of the course Text Mining (732A92) which is part of the Statistics and Machine Learning Master programme at Linköping's University in 2020/2021. The course web page can be found at https://www.ida.liu.se/~732A92/lectures.en.