RunwayML Week 1 Class Notes
Taught by Derrick Schultz & TA Lia Coleman
🔗 Links
💥 This class's objectives
- Learn through making stuff.
- Understand basic machine learning (ML) concepts— Having a basic understanding of ML will help you know what you're doing in Runway!
👩🏫 Class Expectations
- Expect 3-6 hours of homework every week.
- Different ways to approach this class:
- Follow along each week, do every homework assignment, OR
- Follow along each week, work on one big project, OR
- Soak it in, ignore homework (don't recommend, but!)
🖼 AttnGAN demo

- Demir observation: The image generated as the sentence was typed in.
- Takeaway: This model sucks!! It doesn't do well on abstract sentences. It only works well on sentences it was trained on.
- "the car was parked by the beach" is the best it'll do, pretty much. 💩
- Most state-of-the-art models do not produce good images off the bat.
- How was it trained?
- It was trained on birds, dogs, cars, beaches.
- The dataset it got was: People got a bunch of images, then they captioned them. This is what it was trained on.
- In testing, we are doing the reverse: inputting a sentence to get an image.
🤔Moises: How is it working under the hood?