K-means clustering algorithm using MapReduce.

AsanaAi extends its reach to Android devices, offering users the convenience of fitness and wellness on the go. Leveraging TensorFlow Lite for pose estimation and K-means clustering for accurate exercise counting, the Android app ensures seamless integration of AI technologies into users' daily routines, making fitness more accessible and engaging

Basic Machine Learning algorithms from scratch (numpy)

Machine Learning algorithms

A visualization project aims to build trust between regular citizen and government.

Python implementation of K-Means Clustering algorithm for unsupervised learning. Efficiently groups data points into clusters based on similarity. Simple yet powerful tool for data exploration, segmentation, and pattern recognition tasks in various fields.

DocClusterizer is a Java desktop application designed to analyze and cluster documents based on their content similarity. The application utilizes Lucene and Tika libraries to process various file extensions such as txt, pdf, docx, and pptx.

Implementation of K-means algorithm using Hadoop and Mapper side join.

A Python framework for automated clustering analysis using the K-means algorithm.

Using K-means clustering, I will gain insights into similarity between countries and regions of the world by experimenting with different cluster amounts. What do these clusters represent?

This program uses algorithms to efficiently segment textures in images.

Cryptocurrency clustering is the process of categorizing cryptocurrencies into groups based on shared characteristics or features, aiming to reveal patterns and similarities within the cryptocurrency market.

Codes for Practical experiments of Data Warehousing and Mining (Semester V - Computer Engineering - Mumbai University)

This repository houses Python implementations of foundational machine learning algorithms.Each algorithm file or Jupyter Notebook demonstrates the application, functionality, and usage of these algorithms in Python.

webapp clustering using kmeans algorithm

This project showcases my expertise in creating a model adept at distinguishing real banknotes from counterfeit ones, utilizing a rich dataset provided by the organization.

Projeto baseado em dataset de notas verdadeiras e falsas para validação através webapp datadriven.

Repository for various clustering projects including mall customer segmentation and more. Explore data analysis and clustering techniques

KMeans-Client Algorithm implemented in C++: This program receives data using nlohmann JSON and establishes a connection to the server through sockets