<p>The course will cover the following topics: <br/>

(1) Learning features: A structured model.

Introduction to clustering and features extraction. Learning a model using regression and logit regression. Sparsity in high dimension.</p><p>(2) Automatic representation learning with Non­Negative Matrix Implementation.

Matrix factorization and SVD methods. NMF. Completion using NMF and recommendation.</p><p>(3) Using spark, hadoop.

Principle of map reduce. Divide and conquer method. Stochastic gradient optimization.
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(4) Application to movie lens recommendation<font color="#0000ff"><b>.</b></font>

Admission is limited to 24 students (contact: tasio@eio.uva.es)
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