https://github.com/chaitanyac22/neural-network-using-numpy
Introduction to Neural Networks (Create a neural network using Numpy)
https://github.com/chaitanyac22/neural-network-using-numpy
accuracy activation-functions backpropagation-learning-algorithm feed-forward loss mnist-classification model neural-networks neural-networks-from-scratch numpy prediction python3
Last synced: 30 days ago
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Introduction to Neural Networks (Create a neural network using Numpy)
- Host: GitHub
- URL: https://github.com/chaitanyac22/neural-network-using-numpy
- Owner: ChaitanyaC22
- License: mit
- Created: 2021-03-11T18:45:08.000Z (about 5 years ago)
- Default Branch: chai_main
- Last Pushed: 2021-07-09T18:28:42.000Z (almost 5 years ago)
- Last Synced: 2025-06-14T15:03:36.301Z (11 months ago)
- Topics: accuracy, activation-functions, backpropagation-learning-algorithm, feed-forward, loss, mnist-classification, model, neural-networks, neural-networks-from-scratch, numpy, prediction, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 15.8 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Neural-Network-using-Numpy
Introduction to Neural Networks (Create a neural network using Numpy)
In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, loss computation, backpropagation, weight updates etc.
You will use the MNIST dataset to train your model to classify handwritten digits between 0-9.
The assignment is divided into the following sections:
- Data preparation
- Feedforward
- Loss computation
- Backpropagation
- Parameter updates
- Model training and predictions
For Ipython notebook: (Refer to Neural-Networks-using-Numpy.ipynb file)
For the dataset: (Refer to mnist.pkl.gz file)
## Jupyter Notebook Viewer
If you are unable to view or load the jupyter IPython notebook via Github, please click on this [link](https://nbviewer.jupyter.org/github/ChaitanyaC22/Neural-Network-using-Numpy/blob/chai_main/Neural-Network-using-Numpy.ipynb).
Thank you!