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This repository contains code used to create Paper "Navigating Complexity: Evaluating the Effectiveness of Dimension Reduction and Clustering Approaches on Challenging Datasets" as a Bachelor's thesis for EUR.
Assignment 2 – Dimensionality reduction and text classification: converted news text into a machine readable representation, reduced the dimensions of the text representation and trained classifiers to decide which of 20 news groups a sample belongs to.
This is a small project for Big Data Computing course, applying Dimensionality Reduction, Sampling and Clustering for topic detection in text documents.
MushPy project is a Data Science project carried out as part of the Data Scientist training at DataScientest. It has the main objective to create recognition models to classify mushrooms
Pipeline Consisting of LSTM + Variational and Transformer Based Autoencoders + PCA/UMAP (Parameterized and Non-Parameterized) For Generating Low-Dim Manifold Representation of V1 Neural Activity