[therobot24]

really nice visual, it'd be cool to see similar illustrations for areas of ML that do more than just separate classes based on a set of features, rather work with your data in more interesting ways (e.g., CNNs learning features, semi-supervised methods for training with unlabelled data, and subspace techniques like CCA that work on a projected version of your data).

[tonyhschu]

Thanks! Yeah absolutely. We are working our way up to those. Our tentative plan is to tackle bias-variance trade-off next, then random forests, then neural networks.

[therobot24]

oh for sure, just jumping in to these topics is difficult enough. i'm looking forward to what you guys put together next