How many lines of code does it take to train a deep learning model?

Six, if you know which ones.

Check out the secret sauce for training a savvy deep learning model to spot pets in pictures:

	from import *
path = untar_data(URLs.PETS)
dls = ImageDataLoaders.from_name_re(path, get_image_files(path/'images'), pat='(.+)_\d+.jpg', item_tfms=Resize(460), batch_tfms=aug_transforms(size=224, min_scale=0.75))
learn = vision_learner(dls, models.resnet50, metrics=accuracy)
learn.path = Path('.')

When I mentor AI novices, they often do a double-take at how little code it actually takes to kickstart a formidable deep learning machine. People have these wild notions about deep learning, thinking it’s all about:

  • A boatload of complex math
  • An ocean of data
  • A wallet-draining supercomputer setup

But here’s the reality check:

  • Basic high school math will do the trick
  • We can make do with just a pinch of data
  • And guess what? Most of the heavy lifting can be done on freebie computing resources

Get ready to craft some mind-blowing AI apps in our FastAI coaching program. We’ll arm you with the skills to build top-notch deep learning models. All you need is a minimum of one year’s experience in Python programming. Shoot us a message on WhatsApp now to snag your spot!