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Unified and efficient Machine Learning
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Mentors: Student: Yuhui Liu
<p>Refactor the base class Machine API, Add Composite and so on.</p>
Mentors: Student: Tej Sukhatme
<p>This project aims at showcasing Shogun’s capabilities as well as making a <strong>web tool</strong> and an <strong>API</strong> that everyone can use so as to be able to successfully estimate the number of people suffering from <strong>influenza-like illnesses</strong>. First, the current Shogun <strong>regression algorithms</strong> will be utilized to make predictions. Following this, a new algorithm i.e <strong>Poisson Regression</strong> will be used in accordance with a research paper written by <strong>McIver and Brownstein</strong>. All this will be packaged into a <strong>docker</strong> container and uploaded onto the internet. Also, a web API and a web interface with several <strong>visualizations</strong> will be made so as to be able to view this data and these estimations.</p>