Generate Cartoon Images using Generative Adversarial Network. Generator learns to make fakes that look real. Discriminator learns to distinguish real from fake.
Gathered all POI using Overpass Python wrapper. Preprocessed the dataset. Removed outliers from the dataset using DBSCAN. Created clusters based on amenities and plot the polygons on Google Maps.
Extracted face embeddings for each face in the dataset using pretrained OpenFace model. Trained a Neural Network to recognize faces with an accuracy of 90%.
Implemented Sendgrid for sending account verification emails. Used Strip API for receiving card payments from users and AWS S3 Bucket for storing images in production.
Extracted and segmented hand region from live video by thresholding. Count the number of fingers from the segmented hand region by using Convex Hull.
Achieved real-time messaging by implemented WebSockets with Action Cable. Used Devise gem for authentication. Used Semantic UI framework for front-end development.
A web app built using RoR in which users can track stock prices and follow particular stocks according to their choice. User can also connect other users and look up their stocks.
Developed a system that predicts the sentiment of Twitter users towards a specific event/keyword. Collected live tweets using Twitter Streaming API, used NLTK for tokenizing and TextBlob for classification.
Data Scientist | Full Stack Developer
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