SAGAR MANDIYA
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Recent Projects
Answer Verification System
A Deep Learning based model with capability to verify the integrity and correctness of an answer provided in an interview use-case.
Speech synthesis
A Deep Learning based model capable of converting speech present in audio signals into text format using nvidia NGC stack.
Virtual Perimeter Overlay
A Deep Learning based model capable of detecting the boundary advertisements in a soccer game and replacing them with new more appropriate advertisement.
DeepFake Detection
A Deep Learning based model capable of detecting computer generated fake images and videos from the real ones. Thus can help with the widespread of misleading information currently occupying a considerable chunk of online media.
Face Mask and Social Distancing Detection
A Computer Vision based project, encouraging Covid-19 guidelines by detecting social distancing and proper face mask applications, thereby helping in reducing the impact of Covid-19 outbreak.
Movie Recommendation System
A Deep Learning based model capable of recommending movies with the help of various factors like IMDB rating, Genre, etc.
Sentiment Analysis
A Deep Learning (Bi-directional LSTM) based model capable of detecting sentiments, from the public movie reviews posted on the IMDB.
Face Recognition
A Deep Learning based model capable of recognizing faces, which are already in the database. Thus can be used for Home security camera.
Sarcasm Detection in News Headlines
A Natural Language Processing (Bi-directional LSTM) based model capable of detecting human emotions from the text.
Covid Vaccine Finder
A python script capable of notifying the user, when an open slot of desired vaccine is available, while also sending the OTP automatically to save time.
ToDo List React App
This was just a small project meant for learning React. In this project a React web app is built to store and delete ToDos list items. which can be hosted on any server.
Hand Written Digit Recognition
A Deep Learing based model built from scratch, capable of recognizing hand written digits with an accuracy of 99%.
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