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An introductory course on building ML applications with primary focus on supervised learning. Covers the typical ML application cycle  Problem formulation, data definitions, offline modeling, platform design. Also, includes key tenets for building applications.
Note: This is an old slide deck. The content on building internal ML platforms is a bit outdated and slides on the model choices do not include deep learning models.
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