Deep Learning / Spring 1398 (2019)
Announcements
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We’ve gathered a list of final projects (and the featured ones). You can find them on the [Final Project] page.
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LaTeX templates for the Final report are ready, You can download them at the [Final Project Guidelines] page.
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We’ve uploaded the solutions for assignment 1-4, They are available on the [Assignments page].
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Deadlines for the final project are updated. Please check out the new vesrion [Final Project].
- New Assignment released: [Assignment #5 - RNNs in Depth]
- New Assignment released: [Assignment #4 - NLP Intro]
- New Lecture is up: Generative Deep Learning [slides]
Course Description
This graduate course is a dive into applied deep learning. The students will learn how to implement and train neural networks in a variety of tasks across image, sound, and text processing. As a prerequisite, the students are expected to have a basic knowledge of neural networks and be familiar with the concepts behind their structure and training (backpropagation, etc).
Register to our Google groups page to get course notifications via email.
Course instructor
Mohammad Taher Pilehvar
