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Some NN implementations for image classification and neural machine translation

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Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
LICENSE		LICENSE
README.md		README.md
demo_cnn_3d_classification.ipynb		demo_cnn_3d_classification.ipynb
demo_cnn_basic_cifar10.ipynb		demo_cnn_basic_cifar10.ipynb
demo_cnn_resnet_cifar10.ipynb		demo_cnn_resnet_cifar10.ipynb
demo_fc_from_scratch.ipynb		demo_fc_from_scratch.ipynb
demo_nmt_seq2seq.ipynb		demo_nmt_seq2seq.ipynb

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nn_basic

This repository contains some basic NN implementations for image classification and neural machine translation.

1. Fully-connected neural network from scratch

Codes

demo_fc_from_scratch.ipynb

Requirements

Python 3
NumPy

2. Image classification with a basic CNN

demo_cnn_basic_cifar10.ipynb

Requirements

Python 2.7
PyTorch
NumPy

3. Image classification with ResNet

demo_cnn_resnet_cifar10.ipynb

Requirements

Python 2.7
PyTorch
NumPy

4. Neural machine translation with seq2seq model

demo_nmt_seq2seq.ipynb

Requirements

Python 2.7
PyTorch
NumPy
NLTK

5. CNN to classify large 3D regions

demo_cnn_3d_classification.ipynb

Requirements

Python 2.7
Keras (TensorFlow backend)
nibabel (interface to nifti files)
scikit-learn

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