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Neural Network

Neural Network Implementation using Gradient Descent algorithm, Linear Algebra, NumPy, and Matplotlib. The corresponding PyTorch code is also implemented.

Usage

Running the program

jupyter notebook

Running via Docker

Build the JupyterLab Docker image and start it

docker build -t neural-network .
docker run --rm -p 8888:8888 -v "$(pwd)":/home/jovyan/work neural-network

Open JupyterLab at the following URL: http://127.0.0.1:8888/lab

Running via Docker Compose

Start the Docker image

docker compose up --build -d

Open JupyterLab at the following URL: http://127.0.0.1:8888/lab

Clean up the Docker container

docker compose down --volumes --rmi local

Program Output

Numpy Neural Network Implementation

Neural Network without ML Library

Neural Network Weights Visualization

Neural Network Weights with PyTorch

Neural Network Weights Backpropagation

Neural Network Backpropagation with PyTorch

Neural Network Backpropagation with PyTorch 2

Pytorch Implementation

Neural Network with PyTorch

References

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Neural Network Implementation using Gradient Descent algorithm, Backpropagation, Linear Algebra, Activation Functions, NumPy, and Matplotlib

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