Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
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Updated
Feb 10, 2021 - Python
Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
Performance-portable geometric search library
Visualization of many Clustering Algorithms, via Notebook or GUI
A Fast Parallel Algorithm for HDBSCAN* Clustering
Fast and Efficient Implementation of HDBSCAN in C++ using STL
Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).
Genie: Fast and Robust Hierarchical Clustering with Noise Point Detection - in Python and R
This is a python Coursera guided project successfully completed by me.
EIGEN FREQUENCY CLUSTERING USING [KMEANS] [KMEANS & PCA ] [DBSCAN] [HDBSCAN]
Offline and online (i.e., real-time) annotated clustering methods for text data.
Making word clouds more interesting
Data Mining project 2020/2021 @ University of Pisa
NLP on Korean news articles. Automatic topic extraction through dynamic clustering.
Defines a boundary around cluster centers in a given point-layer shapefile.
Implementation of statistics algorithms for Machine Learning & Data Mining. The algorithms were implemented with the Scikit-Learn Library
Optimize clustering labels using Silhouette Score.
My solution for Kaggle NYC Taxi Fare Prediction ( ranked 21st/1463)
NeuralMap is a data analysis tool based on Self-Organizing Maps
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