I am encountering an error while trying to register a model in the Azure ML Workspace. The error occurs in the following code snippet:

I have got 2 components in Azure Machine Learning.
I have got 2 dataframes in the first component (called prep) which I want to pass into the next component (called middle) for further processing.

I have got 2 components in Azure Machine Learning.
I have got 2 dataframes in the first component (called prep) which I want to pass into the next component (called middle) for further processing.

I have got 2 components in Azure Machine Learning.
I have got 2 dataframes in the first component (called prep) which I want to pass into the next component (called middle) for further processing.

I created a dataasset using the python azure API using the code below. The pattern is as following:

When I start a compute instance in an azure ml studio notebook, my kernel selection says “No kernel connected” and more importantly, the drop down where you are supposed to select a kernel is grayed out and cannot be opened. I also cannot open a terminal to check which kernels are loaded; every time I try to access the terminal I just get a “Terminal not available” message.

ImportError: /root/.cache/torch_extensions/py38_cu121/_pvcnn_backend/_pvcnn_backend. so: cannot open shared object file: No such file or directory We have written the python code for training the model (lidar data). While running the code in the Azure ML. FYI: Do you need the code snippet related to this package. azure azure-machine-learning-service

I have a data asset in azure machine learning.
This is of type folder and the folder contains 4 different files with different schemas.
when I consume this data asset in the azure ML notebook, it treats the different files as partitions and messes up the schema.
I want to select individual files while pulling into the notebook.