3. Start the machine and open a terminal in the browser.
4. Run the following command to setup up the tools used for development viz. CUDA, Anaconda, PyTorch and FastAI:
curl http://files.fast.ai/setup/paperspace | bash
This can take a long time. When it’s done, make sure to reboot the machine.
5. Enter the
fastai directory and start Jupyter notebook:
6. Copy the URL shown on the screen, and change
localhost to the public IP of your machine, then paste it a new browser tab. This should open up the Jupyter notebook:
7. Go to
courses/dl1/ and create a new notebook called
8. Copy and execute the following code:
If you see something similar to the following output, you’re good to go:
At this point you’ve successfully trained a cats vs. dog classifier with over 99% accuracy. 🎉🎊🏆
9. If you’re new to deep learning, or are totally lost about what just happened, you can now start watching the first video from Practical Deep Learning for Coders, starting around the 13-minute mark:
This article basically summarizes the first 13 minutes of the above video as text for easier reference.