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Sahil Pethe's Projects

big-data-movie-recommendation-system icon big-data-movie-recommendation-system

Movie recommendation system consisting of the recommendation algorithm written in python which used k-means clustering along with euclidean distance to find out movies similar to a movie given as input. This was done using PostgreSQL server as backend which stored all the movie database information and Django as the front end for displaying the results in a webpage and taking user inputs.

cloth-simulation-with-effects icon cloth-simulation-with-effects

This is a project using the processing which is a 3D API similar to OpenGL but uses Java to enable rapid prototyping of low level code while maintaining a certain higher level of abstraction not observed in OpneGL. This project is a collection of cloth simulation with effects such as wind, object collision and tearing of cloth, all done in Processing using Toxiclib library for particle physics.

distributed-file-system icon distributed-file-system

This file system acts similar to Network File System (NFS). A server master/slave architecture was developed wherein slave server failures (using heartbeat), file replication, file reallocation and file consistency in the slave servers were handled dynamically and asynchronously. Files could be of any size with any number of files. Was developed using Java’s File I/O class and multi-threading.

distributed-publisher-subscriber-system-for-news-articles icon distributed-publisher-subscriber-system-for-news-articles

This is a distributed pub/sub system with an event manager and where each user can be a publisher as well as a subscriber. A user can go offline and come back online asynchronously. The user has the option to subscribe/unsubscribe to any news article at any point of time. Any new notifications will be transmitted to

sudoku-recognizer-using-ocr icon sudoku-recognizer-using-ocr

This is a Sudoku recognizer which uses image segmentation, line matching and then uses Matlab's OCR engine to recognize the numbers in each cell of the matrix with a certain degree of confidence and then output the number recognized

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