Code-First Programming with Azure ML

[@caiyu538]

Great to revisit

[@MartyAckerman310]

another great video, thanks Kevin. btw @9:48, most Pandas dataframe methods operate column-wise by default. So you can just do *df.nunique()* and get the same output

[@ShikharDadhich]

Wow this is exactly what I was looking for. Great video, great explanation, just an amazing experience. Thanks a lot for your video.

[@Cor-tex]

At which point do you choose the GPU you want to use to train a model? Meaning, where is the list of GPUs I could choose from?

[@KevinFeasel]

That happens when you choose the Azure ML compute instance, which is at 6:35 in the video. That works because I've already set up the compute instance in a prior video in the series. To set one up, go to ml.azure.com and connect to your Azure ML workspace. Then, navigate to Compute and make sure the Compute instances tab is selected. Select the New button and you get a menu of available CPU and GPU options. As a quick note, trial accounts and free credits (like from Visual Studio subscriptions) won't have access to any GPU options, but you can at least see the GPUs that are available and if you are using a paid account, you can request quota for the setup you want.