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[P] Training an Image Classifier Using Modern Best Practices

Hi everyone. I recently trained an image classifier on a Japanese character dataset called KMNIST and achieved 97% validation accuracy within a few minutes using a suite of modern deep learning tools and techniques.

I explain all the techniques my blog post, published on the weights and biases site.

I kept this article relatively short and straightforward, so it should be quite accessible to beginners and is likely to improve the performance of your deep learning models.

Primarily, I used the learning rate finder and 1cycle learning rate policy taught by Jeremy Howard in the fast.ai practical deep learning for coders course along with visualization and monitoring tools from a library called Weights & Biases.

Hope you enjoy (and your poor GPU that’s been computing for days) it!

submitted by /u/iyaja
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.