Streaming Anomaly Detection Solution by using Pub/Sub, Dataflow, BQML & Cloud DLP

Personalized real-time movie recommendation system

K-means MapReduce implementation

Using Maching Learning KMeans Algorithm to reduce image colors and compress

Selective search partitions large scale dataset into subsets(shards) such that only few shards needs to be searched for a query, thus improving search efficiency and effectiveness

kmeans

Distributed development applied to KMeans clustering algorithm using Hadoop and Spark.

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

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.

Implémentation de l'algorithme de clustering k-means en utilisant le framework Hadoop version 3.1.3 (MapReduce).

B.Tech. Major Project

TP d'analyse et de classification de données

A mobile application that allows the end user to take a picture with his device, this picture will be processed by means of the K-Means clustering algorithm and then the segmented image will be returned, offering also the possibility to store it in the device.

Offline process RDF Triple on Hadoop ; Online query SPARQL with MPI (Thrift to HBase)

A java implementation of image segmentation using k-means clustering, an unsupervised machine learning algorithm

k means using Hadoop library

Implementation of K-Means Algorithm from scratch in Java

Text mining in Java

Estimating the number of clusters in a data set via the gap statistic. Implemented in H2O-3

Underwater Mine ID platform designed for use by the Navy & implemented with Hadoop, Oracle DB, Apache Tomcat, and a K-Means Clustering + DBScan algorithm