Neural networks in JavaScript – free 19-part course

Post by make3 » Wed, Dec 26, 2018, 7:40 AM UTC

axel180 wrote: post #68

make3 wrote: post #39

Earlier quoted context omitted.

afaik it's mostly for cool demos and educational purposes, or extremely latency intensive applications that funny require large models. for most deep learning models, training on the client is completely unreasonable, as they require weeks of training even on multi thousand $ pro equipement. For training, tiny metalearning models are the only reasonable thing to train on the clients in most useful scenarios, as they…

Keep in mind that while the tutorial is in javascript, in the web browser, the neural network easily apply for node based solutions as well. We're adding GPU support that use either client side OR server side GPU, so that any case you mention can be handled.

Post by Rotten194 » Fri, Dec 28, 2018, 3:26 AM UTC

axel180 wrote: post #64

Rotten194 wrote: post #37

I just watched the reinforcement learning video and was very confused -- where did the reinforcement learning happen? I thought reinforcement learning was giving an agent positive / negative signals to learn without example output data, but in the video the network was just retrained with more data? Is it an overloaded term maybe?

Ty for asking this question! "Reinforcement learning" has a wide definition, but in this case because we are using a simple feed forward neural network, "reinforce" is more principled by dynamic programming with supervised learning. We are not actually using a "Deep reinforcement learning" algorithm. The idea here is that the net can continue to train, reinforcing its previous understanding with new understandings, i…