Anthony Vann CMPE 255 Clustering

a) K-Means clustering from scratch

https://colab.research.google.com/drive/1wovnvddxafXsBHvYRyculJTO1Do4pDe7?usp=sharing

b) Hierarchical clustering (not from scratch)

https://colab.research.google.com/drive/1I6DULyXK5OAiOFCgZOrsJQ-ZnTzxK-mT?usp=sharing

c) Gaussian mixture models clustering (not from scratch)

https://colab.research.google.com/drive/1o8-shC35adDoCCjvGRQebnonn2apH9bM?usp=sharing

d) DB Scan clustering (not from scratch) using pycaret library

https://colab.research.google.com/drive/1Z3g3vhjZU4egb-ieJG9BGaMWa0eXVsEB?usp=sharing

e) Demonstrate anomaly detection using pyOD using any usecase

https://colab.research.google.com/drive/1TGCZ4p7NRdKsiy-RJzSkZBIP-EPJ1F5D?usp=sharing

f) Illustrate clustering of timeseries data using pretrained models

https://colab.research.google.com/drive/1u8whJkyURqEV4_DwTT6eY_Bt5gdTXmdN?usp=sharing

g) Write a colab to illustrate clustering of documents. use state of art embeddings (LLM Embeddings)

h) Write a colab for clustering with images using imagebind llm embeddings

https://colab.research.google.com/drive/1JtWbr6K9qXocXRgNf6tmj71MOZ2dTGTP?usp=sharing

i) Write a colab for audio embeddings using imagebind llms