 Welcome to the Enterprise Model Management course. Before I jump into the outline of the course or any introductions, I want to motivate this course and tell you a little bit about why we created it. And I want to do that with an example. So this is a real pull request from a project that I was involved with in open source. This is from the Kubeflow project and our colleague opens a pull request that changes parameters for a model. So in this case he changes the size of the hidden layer, the learning rate strategy, so on and so forth. The person reviewing the pull request says, okay, that's great. The code looks good. But do these new parameters affect the model's performance? And the original author says, yes, I think it does. I think it does improve the performance. But this is just guessing you know we're having a conversation in a pull request and nobody really knows we're just kind of going on faith that that yeah this change affects the model in a positive way and We don't want to do this. We don't want to guess. When you're writing code, you would never write code like this. If you want to change some code, you want to know whether the code is passing tests, whether the code works or not. This has been a big problem in machine learning for a really long time. For the longest time, I actually created lots of different automations that would bring in tests for machine learning into the PR. I kind of created all these tools and all this stuff because this kind of stuff drove me crazy. And thankfully, now we have great tools, and especially Weights and Biases has created lots of different automations and something around something called the model registry, which we'll get into. That makes it to where you don't have to guess and you have a way to have a single source of truth for your models and you have visibility into the model changes so you don't have to review models like this and you don't have to guess and so I'm really excited about this course because we're going to show you tools that will save you a lot of time and that will prevent you from having to do a lot of guesswork. The next thing I want to do is go over the learning objectives for this course. So first, we're going to talk about what enterprise model management is and what are some of the important concepts of model management. Next thing we're going to do is talk about the central feature that enables model management, which is the weights and biases model registry. Next, we're going to talk about my favorite part, which is how to automate your workflows with the model registry with features like webhooks and launch jobs. And this is going to save you lots of time. Next, we're going to get into practical examples of using the model registry with automation, including integration with external ML systems. I just want to take a moment to introduce myself. So my name is Hamil Hussain. I have over 20 years of experience deploying machine learning in various industries. I focused my career a lot on machine learning infrastructure and tools. I've spent a lot of time creating projects in open source. I've been involved heavily with projects such as FastAI, Jupyter, and Kubeflow, either as a core contributor or as a lead developer. And you can find more about me on my website, hamil.dev. So the next thing we're going to get into is the intro to the model registry. And to do that, I'm going to hand it off to my talented colleague, Noah Schwartz, who is the product manager at Weights and Biases. And she's going to talk to you in detail about the model registry. And she is the world's expert on the Weights and Biases model registry. And she's going to tell you everything you would want to know about it and kind of all the moving pieces. So I'll hand it over to her.
Welcome to the Model CI/CD course!
First, lets get into why model management is such an important topic, to motive it let me show you a real-life example from one of my recent projects. In this course, you will learn how to avoid such guesswork and the consequences that follow it by learning the model management techniques, completing your coursework and getting a certificate. 

Learn more about Hamel Husain at hamel.dev.