Resources

1. Introduction to Docker

In part 1 of this 3-part series, we'll show you the basics of Docker. By the end of the video, you'll be able to package your ML model in a neat Docker container.

Don't worry if you've never used Docker before, we'll be guiding you every step of the way.

2. Introduction to KServe

In part 2 of this 3-part series, we'll show you how to use Kserve. By the end of the video, you'll be able to make your model compatible with Kserve, containerise it, and then run inferences on it.

Once the model is ready, we'll be able to deploy it to Highwind!

3. Highwind Deployment Walk-through

In part 3 of 3 of this series, we'll show you how to create your own use cases and assets.

We will deploy the Iris Classifier Model and then see how to use the dataset for the competition.

4. Model Grading and Submitting to Zindi

In this video, we'll guide you through self-assessing your model and walk you through the process of submitting it to Zindi.