14 Commits (81de6ddbcd752b1eb3304634e6b66e1f352f38e2)

Author	SHA1	Message	Date
Shad Amethyst	cb862f12cc	✨ Softmax layer	2 years ago
Shad Amethyst	0c97a65013	🎨 Remove From<f64> requirement in dropout, working bivariate layer, add builder pattern	2 years ago
Shad Amethyst	9b821b92b0	🎨 Clean up NeuraSequential	2 years ago
Shad Amethyst	2edbff860c	🔥 🚚 ♻️ Refactoring the previous layer system ... It was becoming almost impossible to manage the dimensions of the layers, especially with convolution layers. Generic consts are nice, but they are a bit too early to have right now for this use-case. We'll probably be expanding the implementations to accept const or dynamically-sized layers at some point, for performance-critical applications.	2 years ago
Shad Amethyst	cc7686569a	✨ Block convolution, max pooling	2 years ago
Shad Amethyst	a6da11b125	✨ Pooling layers	2 years ago
Shad Amethyst	d7eb6de34e	✨ 1D convolution layer ... Nailed it on the first try :3c (or not, and I'll regret writing this in a few years)	2 years ago
Shad Amethyst	6c1d6874d7	♻️ Implement and transition to NeuraMatrix and NeuraVector, to prevent stack overflows	2 years ago
Shad Amethyst	920bca4a48	🚚 Move files and traits around, extract stuff out of train.rs	2 years ago
Shad Amethyst	b4a97694a6	🎨 Clean things up, add unit tests, add one hot layer	2 years ago
Shad Amethyst	bca56a5557	✨ Re-order arguments of neura_layer, implement softmax and normalization	2 years ago
Shad Amethyst	220c61ff6b	✨ Dropout layers	2 years ago
Shad Amethyst	8ac82e20e2	✨ Working backpropagation :3	2 years ago
Shad Amethyst	7a6921a1c1	✨ 🔥 Semi-working training, although it seems to be only want to converge to zero	2 years ago