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Dhruv Kapu's Projects

booking-system icon booking-system

This repository contains the core classes needed to build a very basic booking system.

custom-text-model icon custom-text-model

This repository contains a custom implementation of the classes in Sci-Kit Learn to make text analysis smoother and more efficient.

dataset-cats-and-dogs icon dataset-cats-and-dogs

This repository contains the raw cats vs dogs data that has been extracted using the given source code

dkm icon dkm

[CVPR 2023] DKM: Dense Kernelized Feature Matching for Geometry Estimation

fl-maps icon fl-maps

The Public Happiness Movement: A platform bringing people and communities together to solve any and all societal issues. This is mostly the React and Meteor half of our platform

gtsfm icon gtsfm

End-to-end SFM framework based on GTSAM

image_classifier-cat-vs-dog icon image_classifier-cat-vs-dog

This repository contains the source code needed to build an image classification model that can classify an image as a dog, or as a cat.

leveragedetfs icon leveragedetfs

Finding a relationship between leveraged ETFs and their non-leveraged counterparts using simulation

linear_regression icon linear_regression

This repository contains everything needed to create a linear regression algorithm

ml-web-app icon ml-web-app

I used Flask, Bootstrap and scikit-learn to build and deploy an ML web application onto the internet.

neuralnetarchitecture icon neuralnetarchitecture

This project involves building a single layer neural network architecture from scratch without using any prominent deep learning libraries that can be used to compute and predict various values.

newsclassifier icon newsclassifier

This project attempts to find a machine learning-based solution to fake news detection

predictionmodel icon predictionmodel

This mini-project focuses on finding a line/curve of best fit for a given dataset using a brute-force method

sentiment_classifier icon sentiment_classifier

This project contains the required code and data set to build a very accurate (92%+) sentiment classifier that can tell if a movie review is positive or negative.

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