Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

Senior Product- A Canvas LMS anomaly detection algorithm

Function to find the optimal number of clusters for k-means analysis using the Elbow Method

JAVA software which use k-means Algorithm in order to sort French ski resort into three clusters (Small Size, Medium Size, Big Size).

This project processes and clusters text data using BERT embeddings, K-means, and dimensionality reduction. Visualizations include t-SNE plots and word clouds. Dataset and embeddings links are provided.

A K Means Algorithm Module I created from scratch, with different parameters and functionality

About Unsupervised Machine Learning-Netflix Recommender recommends Netflix movies and TV shows based on a user's favorite movie or TV show. It uses a a K-Means Clustering model to make these recommendations. These models use information about movies and TV shows such as their plot descriptions and genres to make suggestions.

Used k-means PCA analysis to classify synthetic spectral profiles from sunspots into similar wavelengths, intensity, temperature, etcetera

Unsupervised Machine Learning-Netflix Recommender recommends Netflix movies and TV shows based on a user's favorite movie or TV show. It uses a a K-Means Clustering model to make these recommendations. These models use information about movies and TV shows such as their plot descriptions and genres to make suggestions.