In this tutorial, I will guide you to use google colab for fast.ai lessons.

Google colab is a tool which provides free GPU machine continuously for 12 hours. Even you can reconnect to a different GPU machine after 12 hours.

Here are the simple steps for running fast.ai Notebooks on google colab.

1. Download fast.ai lesson notebooks. from https://github.com/fastai/fastai/tree/master/courses/dl1
2. Login to your Google(Gmail) account in a browser.
3. Go to colaboratory at URL https://research.google.com/colaboratory/unregistered.html
4. A pop-up window will appear, close that window.
5. Upload a new Notebook from your downloaded notebook files on colab (go to File ->Upload Notebook ) whichever lesson you want to work on.
6. Now change your runtime machine to GPU machine and choose the type of python (Python 2 or Python 3) you are going to use by clicking on (runtime -> change runtime type).
7. You can check if GPU running or not by writing the following code:
   
   import tensorflow as tf tf.test.gpu_device_name()

   1 2	import tensorflow as tf tf.test.gpu_device_name()

   
   it should come up with output ‘/device:GPU:0′ 

Now install the following libraries in your notebook by inserting code cells( Insert -> code cell ):

1. Install pytorch using
   
   Shell

   !pip install http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl && pip install torchvision

   1	!pip install http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl && pip install torchvision

2. Install fast.ai using
   
   !pip install fastai

   1	!pip install fastai

3. Install libSM using
   
   Shell

   !apt update && apt install -y libsm6 libxext6

   1	!apt update && apt install -y libsm6 libxext6

Download dataset using bash commands as an example of dogs vs cats dataset

Now you are ready to use fast.ai on google colab.

Enjoy!!!