https://github.com/adijo/multilayeredperceptron
An implementation of a multi-layered perceptron.
https://github.com/adijo/multilayeredperceptron
deep-learning machine-learning numpy
Last synced: 11 months ago
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An implementation of a multi-layered perceptron.
- Host: GitHub
- URL: https://github.com/adijo/multilayeredperceptron
- Owner: adijo
- Created: 2019-02-09T16:16:37.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-04-23T01:28:35.000Z (almost 7 years ago)
- Last Synced: 2025-02-01T08:14:21.283Z (about 1 year ago)
- Topics: deep-learning, machine-learning, numpy
- Language: Python
- Homepage:
- Size: 21.6 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Multi Layered Perceptron
# Setup
* Set up a `virtualenv`. To install `virtualenv:`
```
pip install virtualenv
```
Then create a virtualenv, maybe called `venv`
```
virtualenv venv
source venv/bin/activate
```
* Install requirements:
```
pip install -r requirements.txt
```
* Setup `PYTHONPATH` to contain `src/` and `dataset`.
* Run tests
`nosetests -v test/`
* To upload experiment results to `comet.ml`,
* Create a `comet.ml` account.
* Export `COMET_API_KEY`, `COMET_WORKSPACE` and `COMET_PROJECT_NAME` variables and run `experiments.py`
# Sample Experiment
