CSCI 5527: Deep Learning: Models, Computation, and Applications

3 Credits

This course introduces the basic ingredients of deep learning, describes effective models and computational principles, and samples important applications. Topics include universal approximation theorems, basics of numerical optimization, auto-differentiation, convolution neural networks, recurrent neural networks, generative neural networks, representation learning, and deep reinforcement learning. Prerequisite: CSCI 5521 or equivalent Maturity in linear algebra, calculus, and basic probability is assumed. Familiarity with Python is necessary to complete the homework assignments and final project.

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A- Average (3.779)Most Common: A (56%)

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183 students
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    /5

    Recommend
  • 2.45

    /5

    Effort
  • 4.14

    /5

    Understanding
  • 3.62

    /5

    Interesting
  • 3.64

    /5

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