https://github.com/kblake/neural_network_elixir
Neural network written in Elixir
https://github.com/kblake/neural_network_elixir
elixir elixir-lang neural-network
Last synced: 9 months ago
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Neural network written in Elixir
- Host: GitHub
- URL: https://github.com/kblake/neural_network_elixir
- Owner: kblake
- Created: 2016-02-20T01:52:18.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2020-02-11T17:24:02.000Z (almost 6 years ago)
- Last Synced: 2025-02-19T01:11:17.449Z (11 months ago)
- Topics: elixir, elixir-lang, neural-network
- Language: Elixir
- Size: 263 KB
- Stars: 115
- Watchers: 7
- Forks: 22
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Neural Network
A neural network made up of layers of neurons connected to each other to form a relationship allowing it to learn.
After cloning:
$ mix deps.get
$ mix compile
## Usage
Run the trainer and see the network learn using OR GATE data
$ mix learn or
You should see output like this:
OR gate learning *********************************************
Epoch: 0 Error: 0.0978034950879825143
Epoch: 1000 Error: 0.0177645755625382047
Epoch: 2000 Error: 0.0065019384961036274
Epoch: 3000 Error: 0.0032527653252166144
Epoch: 4000 Error: 0.0019254900093371497
Epoch: 5000 Error: 0.0012646710040632755
Epoch: 6000 Error: 0.0008910514800247452
Epoch: 7000 Error: 0.0006602873040322224
Epoch: 8000 Error: 0.0005081961006147329
Epoch: 9000 Error: 0.0004028528701046857
Epoch: 9999 Error: 0.0003270377487769315
Epoch: 10000 Error: 0.0003269728572615501
**************************************************************
Run the trainer and see the network learn using IRIS FLOWER GATE data
$ mix learn iris_flower
You should see output like this:
IRIS_FLOWER gate learning *********************************************
Epoch: 0 Error: 0.0164425788515711185
Epoch: 1000 Error: 0.027344153205250403
Epoch: 2000 Error: 0.0265533867778006451
Epoch: 3000 Error: 0.0266624718167679346
Epoch: 4000 Error: 0.0268164947904966262
Epoch: 5000 Error: 0.026857493502782933
Epoch: 6000 Error: 0.026794287038049043
Epoch: 7000 Error: 0.0266556275054049274
Epoch: 8000 Error: 0.0264642981722699525
Epoch: 9000 Error: 0.0262360305030914023
Epoch: 9999 Error: 0.025981881761432242
Epoch: 10000 Error: 0.025981617016649871
**************************************************************
Valid options are: `or`, `and`, `xor`, `nand`, `iris_flower`
Run tests
$ mix test
### Run Console
alias NeuralNetwork.{DataFactory, Network, LossFunction, Layer}
{:ok, network_pid} = Network.start_link([2, 1], %{activation: :relu})
data = DataFactory.gate_for("or")
Network.fit(network_pid, data, %{epochs: 10_000, log_freqs: 1000})
Network.predict(network_pid, [1,1])
### Huge props
* Levi Thompson [https://github.com/levithomason](https://github.com/levithomason)
* Dev Coop group for support [http://www.meetup.com/dev-coop/](http://www.meetup.com/dev-coop/)
## Installation
[Available in Hex](https://hex.pm/packages/neural_network), the package can be installed as:
1. Add neural_network to your list of dependencies in `mix.exs`:
def deps do
[{:neural_network, "~> 0.1.4"}]
end
2. Ensure neural_network is started before your application:
def application do
[applications: [:neural_network]]
end