TLDR: i want to continue practicing and playing around with the notebooks after the course. What are your tips?
Apologies if this have been asked before but is it possible to replicate these notebooks and run them locally (via jupyter) or cloud (via google colab)?
I understand that there are some caveats to this:
- some of the libraries and datasets may not run (or be available) locally due to their size or compute requirements.
- unless i get a paid colab account, i may not have access to faster gpus.
Tips, suggestions for further practice and experimentation with these notebooks are highly welcome and appreciated! Thank you!
Maybe you can run them on AWS sagemaker if you create an account there!
I am running the notebooks on my local machine and some of the cells take a long time to run but they all run
You can try to run them on colab and it gonna be better so that you can use the free GPU access provided by google colab
Great I might just do that, thanks! Is there any advantage to Sagemaker over Colab?
Fantastic! Great to hear this!
I was able to run week 1 and week 2 labs on my local machine, but not week3
I had no problem in running Lab1 at my PC, but for Lab2, I could not get the model from S3 via aws cli. Could you give a tip on that?
You are right, that was a statement ( aws cli ) that I had to execute outside of the Jupyter notebook, because it gave me “aws: command not found”
Another solution that I have tried now is that you activate the python environment under which you are running the Jupyter notebook, e.g. for me it was
conda activate base
Then you install the awscli with the below command
pip install --upgrade awscli
Then I was able to run the cell where it downloads from s3 using awscli
Hope this helps