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Saurabh Katkar's Projects

atm-simulator icon atm-simulator

A Java based simulator consisting of 3 ATM components differing in interface but having similar behaviors integrated using a common ATM framework by implementing Model-Driven-Architecture. Implemented the Output Processor using Strategy pattern, and used Abstract Factory Pattern to select and initialize a list of custom output actions for each ATM.

home-base icon home-base

Strategies to streamline manual data annotation and assessing the annotated labels for correctness

instabot.py icon instabot.py

Instagram bot. It works without instagram api, need only login and password. Write on python.

iterative-classification icon iterative-classification

Implemention of an iterative model for making appropriate predictions using the contents of the links and relations that exist between the links in order to classify unlabeled data more accurately as compared to Content-based Bayesian classification.

main icon main

CS579: Online Social Network Analysis at the Illinois Institute of Technology

product-value-optimization icon product-value-optimization

Given an inventory of commercial products and their features such as condition, value, price etc., maximize wealth by making logical buying and selling decisions so as to obtain maximum profit. Furthermore predict the quality of future products based on products in the inventory by applying different classification algorithms trained using observed data of quality to make predictions on unobserved data.

shortest-path-problem icon shortest-path-problem

Implementation of Dijkstra's algorithm and Bellman Ford algorithm for analyzing their asymptotic behaviour and performance by testing the algorithm on different test cases

twitter-api-sentiment-analysis-project icon twitter-api-sentiment-analysis-project

This project utilizes Twitter API for harvesting tweets concerning Ebola virus and performes sentiment analysis to analyze the level of concern depicted by a Twitter user. We then implement Logistic Regression and Naïve Bayes algorithm to predict political affiliation of Twitter users and compare the performance of the two algorithms.

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