Not the parent, but NNs typically work better when you can't linearize your data. For classification, that means a space in which hyperplanes separate classes, and for regression a space in which a linear approximation is good. For example, take the circle dataset here: https://playground.tensorflow.org That doesn't look immediately linearly separable, but since it is 2D we have the insight that parameterizing by... - Source: Hacker News / 3 months ago

For visualisation and some fun: http://playground.tensorflow.org/. - Source: dev.to / 5 months ago

Https://seeing-theory.brown.edu/ https://www.3blue1brown.com/ https://playground.tensorflow.org/. - Source: Hacker News / 9 months ago

There’s an interactive neural network you can train here, which can give some intuition on wider vs larger networks: https://mlu-explain.github.io/neural-networks/ See also here: http://playground.tensorflow.org/. - Source: Hacker News / 11 months ago

This site is worth playing around with to get a feel for neural networks, and somewhat about ML in general. There are lots of strategies for statistical learning, and neural nets are only one of them, but they essentially always boil down into figuring out how to build a “classifier”, to try to classify data points into whatever category they best belong in. Source: 11 months ago

Hi everyone! I'm Helen, I'm helping out with product and growth at True (NOT Truth Social—completely different product!). We're looking for people to try our free social networking app that's built for small communities. We're especially interested in having the following folks come on board to test it out:. Source: over 1 year ago