Evolving Neural Networks with Particle Swarm Optimization

How to optimize a neural network without backpropagation

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This project was designed to understand the optimization in the neural networks and how we can use other optimization algorithm rather than backpropagation.

We publish an article on the medium of Semantix about this topic.

Semantix Medium Article

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This project was builded with the next technologies.

• Python
• Jupyter
• Pyswarms
• Tensorflow
• Keras

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You need the next componenets to run this project.

• Docker. To install it follow these steps Click. On Ubuntu, you can run:

sudo apt-get install docker-ce docker-ce-cli containerd.io

• Visual Studio Code. To install it follow these steps Click. On Ubuntu, you can run:

sudo snap install code --classic

• Install the visual studio code extension "Remote - Containers"

Follow the next steps:

1. Run the visual studio code.
2. Open the folder where you clone the repository.
3. Click on the green button with this symbol in the bottom left of visual studio code "><".
4. Click on reopen in a container.
5. Execute "experiments.ipynb" notebook.

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Distributed under the GNU v3 License. See LICENSE for more information.

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Esteban Vilca - @ds_estebanvz - esteban.wilfredo.g@gmail.com

Project Link: https://github.com/estebanvz/backpropagation_pso

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