https://github.com/kkiani/xor-tensorflow
Simple implementation of XOR with Tensorflow
https://github.com/kkiani/xor-tensorflow
deep-learning tensorflow tensorflow-examples
Last synced: about 2 months ago
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Simple implementation of XOR with Tensorflow
- Host: GitHub
- URL: https://github.com/kkiani/xor-tensorflow
- Owner: kkiani
- Created: 2018-08-04T13:39:02.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-08-04T15:05:44.000Z (almost 8 years ago)
- Last Synced: 2025-10-26T22:28:10.136Z (8 months ago)
- Topics: deep-learning, tensorflow, tensorflow-examples
- Language: Python
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# XOR Tensorflow
## Overview
This is simple use of tensorflow for classifying XOR gate.
## How to run?
* installing tensorflow using pip: `sudo pip install tensorflow`
* download project and run `main.py`
## XOR
xor is a logic gate/operator that only is true that number of 1's is odd
| A | B | A XOR B |
| --- | --- | --- |
| 0 | 0 | 0 |
| 1 | 0 | 1 |
| 0 | 1 | 1 |
| 1 | 1 | 0 |
## Using Deep Learning
Since xor can't be classified with one perceptron and need non-linearity for classification adding a hidden layer to neural network can help classification.
## license
The MIT License (MIT)
Copyright (c) 2018 Kiarash Kiani
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.