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Abhishek Dutta's Projects

abhi_list icon abhi_list

Abhi List - Abhishek's List. This is a Computer Graphics Project which provides a Graphics Package of 10 menu driven programs using mouse as user input.

blogpost icon blogpost

Blog app with comments using Ruby on Rails 4.2.3. This app uses Devise gem file for log in features and PaperClip for image upload feature. It also requires ImageMagick software to be installed for PaperClip and image uploads.

ecomm icon ecomm

E-commerce website to perform several functionalities

google-map-react icon google-map-react

universal google map react component, allows render react components on the google map

healthcare-predictive icon healthcare-predictive

This is a Healthcare Predictive Analytics Model to analyze signals from devices to test a patient for alarming diseases. This model using deep neural networks to predict an alarm based on the signals generated from different devices

heatmap.js icon heatmap.js

🔥 JavaScript Library for HTML5 canvas based heatmaps

lottiexamarin icon lottiexamarin

Render After Effects animations natively on Android, iOS, MacOS and TvOS for Xamarin

multiple_face_detection icon multiple_face_detection

Multiple Face Detection tool using MATLAB. It implements tracking multiple objects in real time using WebCam and Kanade-Lucas-Tomasi (KLT) algorithm. It automatically detects and tracks multiple faces in a webcam-acquired video stream.

signmeup icon signmeup

Real-time application to sign up for and manage TA hours.

xweather icon xweather

A weather app for iOS and Android built with Xamarin

youtube_recommender_system icon youtube_recommender_system

We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

youtube_tag_predictor_sentiment_analysis icon youtube_tag_predictor_sentiment_analysis

We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

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