From the course: Full-Stack Deep Learning with Python
Join today to access over 24,400 courses taught by industry experts.
Running MLflow and using ngrok to access the MLflow UI - Python Tutorial
From the course: Full-Stack Deep Learning with Python
Running MLflow and using ngrok to access the MLflow UI
- Now, in the earlier movie I'd mentioned that we are going to be using ngrok to expose our locally running MLflow to the internet so that we can view the MLflow UI and view the tracking parameters and metrics for our model training process. Now, we wouldn't actually need ngrok, had we been running this DNN training for image classification on our local machine. We'd simply install and run MLflow locally. However, because we're using colab for training and we are going to be integrating with MLflow running on colab, we need to expose MLflow running on the colab runtime to the internet. And that's why we are using ngrok. Now in order to use ngrok, we need an authentication key from ngrok.com and that's where I'm headed. You can see here that the ngrok Unified Ingress Platform for developers is a lot more than exposing your locally running server to the internet. But that's the use case that we are going to be using…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.
