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Neural Networks are 200 years old (Legendre and Gauss defined Feed forward neural networks). Deep learning. The real difference between traditional ones and dee
by zitterbewegung 2y ago
Neural Networks are 200 years old (Legendre and Gauss defined Feed forward neural networks). Deep learning. The real difference between traditional ones and deep learning is a hierarchy of layers (hidden layers) which do different things to accomplish a goal. Even the concept of training is to provide weights on the neural network and there are many algorithms to do refinement, optimization and the network design.
- varjag 2y agoGauss did not define feed forward neural networks, it all stems from a tweet of a very confused person.
- mrbungie 2y agoI mean, sure, you can model a simple linear regression fitted via Least Squares (pretty much what they did 200 years ago) with a one hidden layer feed-fwd Neural Network, but the theorical framework for NNs is quite different.
- hervature 2y agoFor Least Squares, you do not even use a hidden layer. Just a single dense layer from input directly to output. You also do not use an activation function (or use the identity activation function). That is, everything that makes neural networks special.