Deep Learning class notes

I started taking the deeplearning 2018 and I want to document my path.


In the videos, Jeremy recommends starting immediately by using but in my case I have an Ubuntu 18.0.4 installation with a Mobile NVIDIA processor, so these are the steps that I took to get it to run:

Since I was using ensorflow GPU (setup following these instructions: )

git clone

cd fastai/

I also had Conda installed so I didn’t just want to run the provided script. Instead, all I need was:

conda env create -f environment.yml

Ran into a bit of a hurdle,

“Found GPU0 Quadro M1000M which is of cuda capability 5.0.
 PyTorch no longer supports this GPU because it is too old.”

Trying to solve folowing this:

OK I followed the instructions to build Pytorch from the source. However, it didn’t work. I tried both version 3.0.0 and 3.1.0

Ultimately what worked was this:

install pytorch cuda91 -c pytorch

Suggested here:

That finally returned torch.cuda.is_available() True

Now the bad news:

RuntimeError: CUDA error: out of memory

That’s as fast as I can take it on My Lenovo P50.

Note, I also attempted to run with CPU-only and it was projecting to take 43+ hours :(