salviosage / Neural-Network-

Artificial Neural Network

This repository contains material related to Artificial neural network.

Table of Contents

Tutorials

in this project ill elabolate more on:

• Perceptrons
• Error function
• Softmax
• Cross Entropy
• Gradient Descent
• Feed Forward
• Back Propagation
• Mean Square Error

Dependencies

To set up your python environment to run the code in this repository, follow the instructions below.

1. Create (and activate) a new environment with Python 3.6.

   • Linux or Mac:

   conda create --name deepl python=3.6
   source activate dl

   • Windows:

   conda create --name deepl python=3.6 
   activate dl

2. Clone the repository (if you haven't already!), and navigate to the main / folder. Then, install several dependencies.

git clone https://github.com/salviosage/neural-network-.git
cd neural-network-
pip install .

3. Create an IPython kernel for the deepl environment.

python -m ipykernel install --user --name deepl --display-name "deepl"

4. Before running code in a notebook, change the kernel to match the deepl environment by using the drop-down Kernel menu.