Harsh Navin Gupta (guptaharshnavin)

guptaharshnavin

Geek Repo

Location:Los Angeles, CA

Home Page:www.linkedin.com/in/harsh-n-gupta

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Harsh Navin Gupta's repositories

Parkinson-Disease-Detection

Parkinson Disease Detection using Machine Learning

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DeepFlowerNet-Flower-Recognition-Using-Keras

Recognition of type of Flower from image using CNN, using Keras with Tensorflow backend

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AbstractIt-Extractive-Text-Summarizer

Summarization of text using Extractive Summarization. Developed using Python with Spacy & sklearn.

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DisasterTweet-Detection-of-Fake-Disaster-Tweets

Classification of Disaster Tweets as REAL or FAKE using Machine Learning

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iSpam-Spam-Message-Detector

Detect whether message is a SPAM or HAM, using Machine Learning Models

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Loan-Approval-Prediction

Developed ML Model to predict whether a loan will be approved or not, based on various parameter, such as Marital Status, Income, etc.

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LR1_Parser

Implementation Of LR1 Parser Using Python 3

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AdmitLab-Graduate-Admission-Forecaster

Predict chances of admission, based on various parameters such as GRE, TOEFL scores and others.

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Global-Terrorism-Analytics-Dashboard

Interactive Dashboard for Global Terrorism Analysis

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Prosper-Loan-Data-Analysis

Analysis of Loan Data from Prosper

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Telecom-Customer-Churn-Analysis-And-Prediction

Predict whether a particular Telecom Customer will Churn or Not ?

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WeRateDogs-Dog-Rating-Tweets-Analysis

Detailed Data Wrangling and Analysis of tweets of Dog Ratings from WeRateDogs.

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Coronary-Heart-Disease-Prediction

Prediction of Occurrence of Coronary Heart Disease using Machine Learning

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Credit-Card-Fraud-Detection

Detection Of Genuine & Fraudulent Credit Card Transactions

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guptaharshnavin

Personal Repository

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Hackerrank_Problem_Solving_Soln

This Repository Contains All The Codes That Have Successfully Executed For Hackerrank Problem Solving Questions

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Medical-Appointments-No-Show-Analysis

Analysis of Medical Appointment No-Shows using Python & Seaborn.

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Movielens_Recommendation_System

For this project, we make use of the Movielens 10M Dataset. The Movielens datasets were collected by the GroupLens Research Project at the University of Minnesota. In this project, we make a Recommendation System, which recommends movies to watch to the users, based on the various features that are present in the dataset, which are the features that are present in the ratings given by other users.

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OnlineHotelBookingSystem

Online Hotel Booking Management System. This repository contains all the files used to implement a web-based interface, connected to a backend database, to implement the desired system. The Web Interface is designed using HTML5,CSS3 & PHP5. The database used in the backend is MariaDB.

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Red-Wine-Quality-Prediction

Prediction Of Red Wine Quality Using Neural Network.

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