MAmade2591·Aug 8, 2017Submission
Show HN: A multi layer perceptron with back propagation in Go [pt 2]
2 points · Open discussionmade2591
go-perceptron-go
Go2017–2017
made2591 / go-perceptron-go
go-perceptron-go
A single / multi layer / recurrent neural network written in Golang.
2Distinct people
5Mentions
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171GitHub stars
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A single / multi layer / recurrent neural network written in Golang.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Jul 31 | 2017-07-31 00:00:00 UTC | 2017-08-01 00:00:00 UTC | 2 | 1 | 1 |
| Aug 1 | 2017-08-01 00:00:00 UTC | 2017-08-02 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2 | 2017-08-02 00:00:00 UTC | 2017-08-03 00:00:00 UTC | 0 | 0 | 0 |
| Aug 3 | 2017-08-03 00:00:00 UTC | 2017-08-04 00:00:00 UTC | 0 | 0 | 0 |
| Aug 4 | 2017-08-04 00:00:00 UTC | 2017-08-05 00:00:00 UTC | 0 | 0 | 0 |
| Aug 5 | 2017-08-05 00:00:00 UTC | 2017-08-06 00:00:00 UTC | 0 | 0 | 0 |
| Aug 6 | 2017-08-06 00:00:00 UTC | 2017-08-07 00:00:00 UTC | 0 | 0 | 0 |
| Aug 7 | 2017-08-07 00:00:00 UTC | 2017-08-08 00:00:00 UTC | 0 | 0 | 0 |
| Aug 8 | 2017-08-08 00:00:00 UTC | 2017-08-09 00:00:00 UTC | 3 | 1 | 2 |
What Hacker News says
5 sourcesI just pushed multi layer perceptron with back propagation algorithm:
https://github.com/made2591/go-perceptron-go
In Show HN: A perceptron with stochastic gradient descent in GoHi All, I dev the multi layer perceptron with back propagation algorithm. If you want to have a look, please go to: https://github.com/made2591/go-perceptron-go
Have a nice day!
In Show HN: A perceptron with stochastic gradient descent in GoCool project! Makes me want to recommend to my brother to start something like this.
Would definitely recommend trying vectorised calculus (instead of calculating the output with loops [0])
I'd also advise you to steer from some apparently neurology-inspired terms (stimulus) and use terms more common in machine learning (vector, features, etc.).
If you want to go further with this, you could try to implement back propagation with different activation functions and any depth. Check CS231n [1], the reference course for this.
[0] https://github.com/made2591/go-perceptron-go/blob/master/uti...
[1] http://cs231n.stanford.edu/
In Show HN: A perceptron with stochastic gradient descent in GoShow HN: A perceptron with stochastic gradient descent in Go
94 points · Open discussion