Hi. I just started with the firat video but there is no way i can get to the terminal in order to download the configuration of fast.ai. How should I do it? thank you
Hi, everyone.
I’m newbie here, and I have a question that which platform (Crestle, Paperspace, AWS) I should use.
I tried the first option of the lecture video, Crestle. But I found it much slower than the video – the lecture says it took 20 seconds to execute the example of lecture 1, but it took several minutes on the Crestle.
I don’t quite understand when watching the lecture, but what is the defference between Crestle, Paperspace, and AWS, and which one is recommended?
I am not so stingy, and don’t mind to pay for GPU server. But I don’t want to wait too much – I want my environment as fast as the lecture video.
thanks!
I would like to get started on the course using my own laptop (instead of Paperspace), I am running Linux and have a NVIDIA GPU. Is the setup the same as if I was setting it up on Paperspace?
@jeremy
Thank you for great lecture on random forests. I have a question on selecting objective function for modeling.
On Kaggle and in various business settings, for regression problems various objective functions are used - RMSE , MAE , log-loss, Mean Absolute Percentage Error (MAPE) etc.
What is the right measure? What is the down side of choosing one over the other? Is selecting one of these a subjective business decision ? Looking forward to hear your thoughts.
Hi @jeremy, I just set up my paperspace account and configured it to the course and had three questions about specific steps w regards to how to proceed. I referenced the GitHub page for the course, Reshamas materials, and the forum posts to try and figure out how my questions, but was not able to find the specific answer and was wondering if I could ask for some additional help?
I was trying to download Github data, set up a separate folder for my jupiter notebooks, and when to involve my local machine when downloading/completing the course.
I am getting an error when I check for kaggle-cli on (fast ai) paperspace@… $ and I tried to install it using Reshamas step by step Github process, but I am getting the following error:
I tried installing kaggle-cli too and still the message reads: '…requires path lib which is not installed…"
How do we ‘clone’ fastai and save our notebooks in a different path like Reshamas has done?
Here are her directions, but when I tried to update my .bashrc I was having trouble doing so.
Option 2: where you want
If you change the default location of your notebook, you’ll need to update your .bashrc file. Add in the path to where you’ve cloned the fastai GitHub repo:
for me, my notebooks are in a “projects” directory: ~/projects
my fastai repo is cloned at the root level, so it is here: ~/fastai
in the file .bashrc add this path:
export PYTHONPATH=$PYTHONPATH:~/fastai
Reminder: don’t forget to run (or source) your .bashrc file:
add path where fastai repo is to .bashrc
save and exit
source it: source ~/.bashrc
For these steps (show below/throughout course), are we suppose to clone fastai on our local computer too or are these additional instructions for the paperspace GPU?
Normal installation
Download project: git clone https://github.com/fastai/fastai.git
Move into root folder: cd fastai
Set up Python environment: conda env update
Activate Python environment: conda activate fastai
If this fails, use instead: source activate fastai
Install as pip package
You can also install this library in the local environment using pip
pip install fastai
However this is not currently the recommended approach, since the library is being updated much more frequently than the pip release, fewer people are using and testing the pip version, and pip needs to compile many libraries from scratch (which can be slow).
The best way I use the latest fast.ai is like this
Have a git clone of the lib itself
Make sure you have installed all the necessary modules.( Just install a couple of big modules as they will install nearly a lot of dependencies, I remember explicitly installing Bcolz,graphviz, space etc…)
And all the notebooks are in the same directory as Jeremy’s are…(you can change this or use fast.ai wherever you want by creating a symlink in that directory)
And now to use the bleeding edge version, I just do git pull in the parent/original colned repo…
I submitted my request to Paperspace on May 22, and waited and waited, but they had not givin me back a word.
Paperspace send me a mail on June 13, that my request has been approved. I never expected I had to wait more than half month – I have waited so long that my motivation has gone away. Please be careful, waiting time can be several weeks.
Hey,
I am also facing the same problem. I created a entropay account and tried to pay through my debit card, when I try to pay I do get OTP on my phone but after entering the OTP and returning back to entropay interface I get error saying “We were unable to top up your Entropay card from this credit or debit card. Please check that your card details (including CVV and expiry) were entered correctly and that you have sufficient funds for this transaction on this credit or debit card.”
I do have sufficient funds in my account and I’ve checked all my credentials and they are correct.
Could you please help me in this regard? How did you pay for your entropay top up?
hi @jeremy. I was looking into the script that we get from setup for fastai. How did source activate fastai work as there was no environment called fastai got created before ?
Can someone help me to get free GPU? I tried google cloud, but there are no free GPUs. Also i tried google colab, even that is busy everytime and has less memory. Even i tried snark, but offer is over. Could anyone please help with the current available and good GPU ?
The google colab method worked for me but the colab instance is dying very quickly. The connection to the clouderizer machine is lost in under 10 min. I am wondering if this is related to my internet connection (around 30 Mbps) or something else.
If anyone else has solved this problem, I would appreciate help.
