Published on June 13, 2019 by

Transfer learning is a statistical technique that’s been getting more attention lately that enables you to reuse a model for a different task than what it was trained for. In this episode, I’m going to show you how to use transfer learning to predict instances of gold deposits using publicly available satellite imagery. We’ll discuss the 4 different mathematical ways to frame the transfer learning problem, then look into how a U-Net architecture works. The U-Net is really popular for image segmentation and classification tasks on sites like Kaggle, so knowing how it works will be a useful skill. Enjoy!

Code for this video:
https://github.com/llSourcell/mapo

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