Performance-portable geometric search library
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Updated
May 23, 2024 - C++
Performance-portable geometric search library
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
Regression, Classification, Clustering, Dimension-reduction, Anomaly detection
Document-level semantic clustering. Unsupervised topic modelling.
The thesis presents the parallelisation of a state-of-the art clustering algorithm, FISHDBC. This objective has been achived by improving the main data structures and components of the algorithm: HNSW, MST and HDBSCAN. My contribution is based on a lock-free strategy, completely wrote in Python.
Genie: Fast and Robust Hierarchical Clustering with Noise Point Detection - in Python and R
Supervised Machine Learning (GNB, Knn, LR, MLP & SVM) in the dataset philippines and Unsupervised Machine Learning (k-means, HAC, GMM, DBSCAN, HDBSCAN & SOM) in the datasets wingnut & h2mg_128_90
Document Clustering, Summarisation and Visualisation on 20NewsGroup
Using BERTopic to show the path of technological advancements in the different phases of the economic cycle (January 2005- January 2023).
Easily identifying themes in text
Pipeline leveraging UMAP and HDBSCAN with BERTopic for large datasets.
Lyrics clustering
Text clustering: HDBSCAN is probably all you need.
A fun Topic Modeling Project of the TV show Stargate SG1
HDBSCAN Tuning for BERTopic Models
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