Atcold/NYU-DLSP21
NYU's Deep Learning Spring 2021 course with slides, notebooks, and practicum assignments on neural network fundamentals and energy-based models.
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This repository hosts the educational materials for NYU’s Deep Learning course, including redesigned lecture slides and Jupyter notebooks. The curriculum covers historical foundations of deep learning, backpropagation and gradient descent, parameter-sharing architectures like recurrent and convolutional networks, and latent variable energy-based models. It serves as the sequel to the previous NYU-DLSP20 release, incorporating a restructured approach to teaching fundamental deep learning concepts.
Frequently asked
- What is Atcold/NYU-DLSP21?
- NYU's Deep Learning Spring 2021 course with slides, notebooks, and practicum assignments on neural network fundamentals and energy-based models.
- Is NYU-DLSP21 open source?
- Yes — Atcold/NYU-DLSP21 is an open-source project tracked on heatdrop.
- What language is NYU-DLSP21 written in?
- Atcold/NYU-DLSP21 is primarily written in Jupyter Notebook.
- How popular is NYU-DLSP21?
- Atcold/NYU-DLSP21 has 1.7k stars on GitHub.
- Where can I find NYU-DLSP21?
- Atcold/NYU-DLSP21 is on GitHub at https://github.com/Atcold/NYU-DLSP21.