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Daniel Agafonov Portfolio

Software Engineer

Danielle Maxwell

This book is suitable for an introductory course of data analytics to help students understand some main statistical learning models, such as linear regression, logistic regression, tree models and random forests, ensemble learning, sparse learning, principal component analysis, kernel methods including the support vector machine and kernel regression, etc. Data science practice is a process that should be told as a story, rather than a one-time implementation of one single model. This process i

David Millard

I'm a software engineer working on audio and music software. My interests include physical modelling, interfaces, dsp, algorithmic composition and installations.