3 ms·
Looking at you, deep learning.
by scottlocklin 6y ago
Looking at you, deep learning.
- api 6y agoThere is probably a ton of isomorphism between different models. It may come down to what is easiest to understand and fastest to implement in code.
- segfaultbuserr 6y agoSee also: A visual proof that neural networks can approximate any function https://news.ycombinator.com/item?id=19708620 https://news.ycombinator.com/item?id=19708620
- api 6y agoSo a "neural network" is actually a type of parameterized mathematical function that can be fit to any curve including higher dimensional surfaces, etc.?
- wongarsu 6y agoA linear SVM can in turn be expressed as a very shallow neutral network. The main difference is that with SVMs you put all your effort into transforming inputs for the model (e.g. all the popular kernels) while with neural networks usually most of the effort goes into clever model architectures.