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Kshitij Bipin Deogade's Projects

albacore icon albacore

Albacore is a professional quality suite of Rake tasks for building .NET or Mono based systems.

find_if_employee_will_leave_company icon find_if_employee_will_leave_company

Based on some features such as Comments made by employee, people supporting him, his last comment data, his company; predict whether he will leave company.

gns3 icon gns3

Make virtual router networks in GNS3 using OSPF and RIP protocols

harmonia_for_b_plus_trees icon harmonia_for_b_plus_trees

Harmonia is an algorithm that allows for the implementation of operations on B+ trees using parallelization. As a part of my GPU project, I implemented the Harmonia paper published in 2019 in CUDA.

hldig icon hldig

hl://Dig is a fork of ht://Dig, a world-wide-web search system for an intranet or small internet.

inference icon inference

Reference implementations of inference benchmarks

make_http_proxy icon make_http_proxy

Proxy takes multiple client connections; recognises GET method, and after parsing URL and converting to relative URL, sends data back to client

netcat- icon netcat-

A paper presentation with slides and video of NetCAT, a way to detect keystrokes in machine by exploiting the optimization of Intel processors to use LLC cache instead of full RAM access

print_tweets_of_last_10_minutes_of_ny_and_ca icon print_tweets_of_last_10_minutes_of_ny_and_ca

This repo has the code for a project we got in our Cloud Computing Course at the Department of Computer Science at IIT Madras. It has code for spinning 2 ec2 instances on Amazon Cloud, detect tweets on Corona coming from NY and CA for the last 10 minutes; feed these tweets to a kafka producer; apply Spark Streaming on these tweets; run the FP-Growth Algorithm on this streamed data; make an online interface having buttons for choosing CA or NY; and printing the most frequent words and number of tweets in the tweets of that respective state selected

run-_als_and_fp_growth_of_spark_mllib icon run-_als_and_fp_growth_of_spark_mllib

On ALS.txt, run MovieLens ALS algorithms, which will need scala's sbt. On FP_Part-1.csv and FP_Part-2.csv, run FP Growth algorithm. In ALS, the number of iterations and regularization parameter are fine-tuned to minimize error.

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