> does not need labeled data
It needed training on 1TB of labeled images in the first place. Arguably it can be used to transfer that knowledge to other tasks with a much smaller amount of labeled samples but still requires supervision.
It needed training on 1TB of labeled images in the first place. Arguably it can be used to transfer that knowledge to other tasks with a much smaller amount of labeled samples but still requires supervision.
If the error rate gets low enough, a NN could start labeling pics.
Finally, recent work has shown that running a dictionary through an image search engine can yield high quality labeled images automatically.
Aside: Thank you for contributing to sklearn. Really feel like I am standing on the shoulders of giants when I use that library.