This page contains links to resources which will introduce you to machine learning and deep learning. We encourage you to go through them in order, at your own pace, and to post any questions you may have on Slack.
This page also contains links to video walkthroughs corresponding to several of our introductory workshops, in case you missed them in-person or wanted a quick refresher.
- What is Machine Learning? [video link]
- What is a neural network? [video link]
- Gradient descent: how neural networks learn [video link]
- (Optional) What is backpropagation? [video link]
Once you have the intuition for what deep learning is, we'll dive in to a hands-on PyTorch tutorial where you'll code your own neural network (within the development environment you set up in the Software Setup workshop). We'll all be working together to get an image classifier up and running so you can see what an end-to-end, albeit simple, deep learning model looks like. The goal here is to give you a good foundation for when you branch off to develop your specific projects!
- Part 1: Exploring the FashionMNIST dataset and designing the model architecture [video link]
- Part 2: Coding the neural network model [video link]
- Part 3: Coding the model training process, running training, and evaluating your model [TBA]