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hierarchical-clustering

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Final year project experimenting with clustering and topological data analysis of scRNA-seq data using Python and R across two Jupyter notebooks

  • Updated Aug 8, 2021
  • Jupyter Notebook

This repository includes Colab notebooks demonstrating various clustering algorithms, from scratch-based methods to advanced deep learning models and embeddings. Each notebook features explanations, visualizations, and quality evaluation metrics for clustering performance.

  • Updated Dec 10, 2024
  • Jupyter Notebook

Notebook desenvolvido como avaliação da disciplina Introdução à Inteligência Artificial. O mesmo contempla partes de pré-processamento das bases de dados e o desenvolvimento dos algoritmos Multilayer Perceptron (MLP), Random Forest, K-means e Agrupamento hierárquico

  • Updated Dec 21, 2020
  • Jupyter Notebook

This repository contains a collection of lab tasks, assignments, and projects designed to learn and practice key concepts in Machine Learning. It includes hands-on Jupyter notebooks covering fundamental ML techniques, real-world projects, and theoretical exercises. Ideal for students and enthusiasts aiming to deepen their understanding of ML.

  • Updated Jan 6, 2025
  • Jupyter Notebook

In this notebook, i have tried to appy KMeans, Hierarchical and DBSCAN clustering along PCA. The dataset used is Mall_Customers. In DBSCAN, certain type of Heatmaps are used to find the Epsilon and min_samples value which have performed quite well in identifying the correct number of clusters.

  • Updated Apr 17, 2024
  • Jupyter Notebook

Jupyter Notebooks exploring Machine Learning techniques -- regression, classification (K-nearest neighbour (KNN), Decision Trees, Logistic regression vs Linear regression, Support Vector Machine), clustering (k-means, Hierarchical Clustering, DBSCAN), sci-kit learn and SciPy -- and where it applies to the real world, including cancer detection, …

  • Updated May 21, 2020
  • Jupyter Notebook

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