L2 regularization term on weights. Increasing this value will make model more conservative. Normalised to number of training examples. alpha (default=0, alias: reg_alpha) L1 regularization term on weights. Increasing this value will make model more conservative. Normalised to number of training exam...
This happened when I added l1/l2 regularizer to a dense layer and intended to save the model with pickle. Many thanks.
The name “supervised learning” is used to describe these types of models because the model learns the underlying pattern on a training set. The number of iterations/rounds determines the number of times the model has a chance to learn from its past. In each subsequent round, the model trie...
The answer, as alwyas, is that it depends. In this post, I wanted to visit use cases in machine learning where deep learning would not really make sense to use as well as tackle preconceptions that I think prevent deep learning to be used effectively, especially for newcomers. Breaking de...
🐛 Describe the bug When compiling flex attention with dynamic=True I receive the following error. This only happens when a BlockMask is used, it works fine with block_mask = None. With dynamic False it works but recompiles for each batch...
); it might use rectifying linear units or other activation functions; it might or might not have dropout (in what layers? with what fraction?) and the weights should probably be regularized (l1, l2, or something weirder?). This is only a partial list, there are lots of other types ...