Deep Learning Intro to Framework and Tools
About
This unit provides an introduction to neural networks and their applications. You’ll start with a conceptual understanding of how neural networks work, explore popular frameworks like PyTorch and Hugging Face, and learn to examine models using model cards. Finally, you’ll examine deep learning applications in domains such as computer vision, natural language processing, and more.
Learning Objectives
You will be able to:
- Understand the fundamental concepts of neural networks.
- Explore common deep learning frameworks (PyTorch, Hugging Face, torchvision).
- Learn how to use model cards to select appropriate models for specific tasks.
- Identify and evaluate real-world deep learning applications across various domains.
Content
| Topic | About |
|---|---|
| Full Lesson Deck | Conceptual introduction to neural networks. |
| 0OP Review | Review of classes in Python |
| Intro to PyTorch | An introduction to PyTorch |
| Activation Functions | visualizing the different activation functions |
Prerequisites
- Basic Python programming knowledge.
- Familiarity with machine learning concepts such as linear and logistic regression.
References
Important note
Please ignore the _layouts folder and the config.yml file in the root of this repo. They are needed to make sure the repo renders well; please don’t change them or delete them and your repo will work fine :)