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igupta967937's Projects

deep-air icon deep-air

Predicting Air Pollution in Beijing, China using Deep Neural Nets

deep-algotrading icon deep-algotrading

A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

deep-learning-v2-pytorch icon deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

diabetes_shinyapp icon diabetes_shinyapp

A Shiny App that demonstrates predictive analytics developed using the tidymodels package with patient data sourced from the UCI Repository Of Machine Learning Database

diabity icon diabity

This website is a one stop solution for Diabetes

disaster-response-pipelines icon disaster-response-pipelines

Created Disaster response pipelines and Web App for classifying text messages received during disaster into response categories, reducing the potential reaction time of disaster response organizations.

disease-prediction-using-machine-learning icon disease-prediction-using-machine-learning

This Machine Learning project is used to predict the disease based on the symptoms given by the user.It predicts using three different machine learning algorithms.So,the output is accurate.It uses tkinter for GUI.

djangowebsite icon djangowebsite

ProductHunt Website with Database.Provided with login logout and signup facility.

drugsrankingpredictionapp icon drugsrankingpredictionapp

Shiny App: Patient's assessment (scoring) of the drug based on review (Naive Bayes, TPOT auto-ML, natural language processing, sentiment analysis)

ecommerce-reviews-analysis icon ecommerce-reviews-analysis

Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)

europeancomission_nlp_networkanalysis icon europeancomission_nlp_networkanalysis

This project was led during my internship at PwC in collaboration with DG EAC and DG Informatics from the European Commission. Their end goal was to use data and machine learning to get insights on education in Europe to help Policy Officers in their decision making. In this context we developed two PoCs (delivered as ShinyApps) which were deployed on the Commissions' severs. The project involved WebScrapping, NLP and Graph Theory. http://34.245.7.232:3838/myapp/poc1/prototype1/

everymood icon everymood

A chat bot app using IBM Watson Assistant's API that allows users to navigate their emotional health with therapeutic conversation.

fake-news-detector icon fake-news-detector

A Fake News Detector web app which inputs the news headlines and tells whether news is fake or real.

faqchatbot-1 icon faqchatbot-1

Set of scripts to build a chatbot which will answer based on the FAQs supplied.

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