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Word Embeddings: Context and Representation
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Related lectures (56)
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Optimization Principles
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Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.
Convolutional Neural Networks: Fundamentals
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Optimization algorithms
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Covers optimization algorithms, focusing on Proximal Gradient Descent and its variations.
Supervised Learning: Classification Algorithms
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Introduction to Machine Learning: Basics and Examples
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Introduces the basics of machine learning, emphasizing the use of Piazza for class-related communications and practical exercises in Python.
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Supervised Learning in Financial Econometrics
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Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
Linear Programming Basics
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