Machine Learning in Computational Finance
This is a collection of assignments for a course on Machine Learning in Computational Finance that I attended. The course gave a survey of machine learning methods in the context of computational finance with the following units:
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Regression and its generalizations (GLM, sparsity, constraints)
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Decomposition methods (SVD, RPCA, NMF)
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Time series models
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Unsupervised/nonparametric methods (e.g. clustering)
The course was a mix of optimization techniques, statistical modeling, and computational finance applications. The assigments covered modeling, theory and computation. I used Python and Julia to do the coding part of the assignments.