Comments (9)
Awesome! The feed forward networks (the current brain.js neural net) won't be able to give a reliable prediction (arguably) because it is trained by what would be easily described as a sort of frozen state, for example: if I were to say "parchment", you'd be like: "that was odd to say, what did he mean by that?".
That being said, it is how a feed forward neural network... work, they don't really have a memory of what is going on to give it a context.
However, a recurrent neural network can recall what is going on. If you are still reading this you will remember I said the word "parchment", and may be further intrigued at where I am going with it. I am not, other than to illustrate that memory is very powerful, especially in predictions.
However (and this brings me a lot of pleasure) the recurrent neural network that is being worked on here has a handy little method... interestingly called "predict", which I believe is what could be used in this scenario.
This code is actively being worked on, but would probably give you a pretty good prediction.
The code is being honed to not only be a "hey look what neural networks can do!" but also be enterprise ready. If we can get the pseudo csv data mentioned above fed into the neural net, certainly a predictive state could be had.
from brain.js.
It will be runs 100% able to run in browser.
from brain.js.
Can you give me an example?
from brain.js.
Weather forecasts, financial predictors, trends. It takes previous entries into consideration when calculating the output.
from brain.js.
Do you have a dataset we could work with?
from brain.js.
This is a very simple example: https://archive.ics.uci.edu/ml/datasets/Dow+Jones+Index
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Wow this is excellent! I'm going to give this a try as soon as I can. Thank you for all that information. It really puts everything into perspective.
Edit: Is there a standalone rnn.js for the browser?
from brain.js.
FYI: https://github.com/harthur-org/brain.js/blob/recurrent/browser.js#L1590
A unit test that predicts maths: https://github.com/harthur-org/brain.js/blob/recurrent/test/recurrent/lstm.js#L15
from brain.js.
The whole library is available here:
https://github.com/harthur-org/brain.js/blob/master/browser.js
and https://github.com/harthur-org/brain.js/blob/master/browser.min.js
These are built frequently, usually when committing. I'm currently working to reduce the complexity of the recurrent neural net, but it is now running in browser, and is fairly stable.
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Related Issues (20)
- Deno Support?
- The Recurrent class will not function without a GPU HOT 1
- Unable to install Brain.js on PopOS HOT 22
- GPU powered AI demo is a 404 HOT 2
- "Forecasting" demo is a 404 HOT 2
- tree process
- Freezing when training NeuralNetworkGPU (async).
- Train with NeuralNetworkGPU more slower than CPU HOT 3
- Always the same output data on NeuralNetwork HOT 1
- Unable to install on MacOS Ventura HOT 1
- Did you try the built in distance calc?
- need to update URL for example
- MacOS node 20.10.0 build failing HOT 2
- Fatal error while installing via NPM package HOT 1
- Most example links are broken HOT 4
- Summary()
- Type 'InputType' is not assignable to type 'Partial<INumberHash>'... and many others
- stream-example.js page not found error HOT 1
- Npm i brain.js || node-gyp error
- Brain.js to detect bad words HOT 1
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