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PennApps17

Built using machine learning (Tensorflow with Keras wrapper) to predict stock prices and derive interesting data visualization with D3.js + ClojureScript to formulate investment strategies. Takes help of sentient analysis of the new feed to tap on the mood of the market. Stock market is an largely based on the actions and decisions of every individual participating in it and every user's action has a n impact on it.

REST API is cooked up using Hasura.io, a Firebase-like PaaS driven by PostgreSQL as opposed to NoSQL.

Team: Jason Lin@GT, Kartikay Goyle@UofT, Gayatri Joshi@CMU, Joe Qian@UCLA

PennApps Top 30 finalist

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Predicting Stock prices using Machine Learning

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