feat: README.md w/ usage, training and inference instructions
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README.md
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README.md
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# Python AutoEncoder from scratch using Numpy
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## Usage
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1. Install requirements :
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```sh
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$ pip install -r requirements.txt
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```
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2. Optionally run mnist_test.py.
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```sh
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$ py mnist_test.py
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```
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## Training
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Instatiate an `Autoencoder` object :
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```py
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from autoencoder import Autoencoder
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autoencoder = Autoencoder(in_len=300, bottleneck=50, 0.001, relu)
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```
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And then via the `train_dataset` method to train over a dataset :
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```py
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autoencoder.train_dataset(data)
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```
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Or via the `train` to input each data points iteratively :
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```py
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autoencoder.train(v)
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```
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## Inference
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Use your `Autoencoder` object with the `encode` and `decode` methods like so :
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```py
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example = ...
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code = autoencoder.encode(example)
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output = autoencoder.decode(code)
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```
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