Algorithms

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for algorithm implementation and testing.

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This is a repository for algorithm implementation and testing.

## Outline

| Algorithm | Description | Link |
| --- | --- | --- |
| EM | Expectation-Maximization Algorithm for parameter esimation. | [Code](https://github.com/fs302/Algorithms/blob/master/EM/expectation_maximization.py)|
| MatrixFactorization| An implementation of matrix factorization | [Code](https://github.com/fs302/Algorithms/blob/master/matrix_factorization/matrix_factorization.py)|
| LSH | Pretty large scale implementation of Locality-Sensitive-Hash. | [Doc](https://github.com/fs302/Algorithms/blob/master/LSH_Application/README.md)|
| Bandit | Contextual bandit algorithm comparation including Greedy epsilon, UCB and Thompson sampling. | [Code](https://github.com/fs302/Algorithms/blob/master/bandit_decision/decision_service_demo.py)|
|LIME| An instance level explainable algorithm framework for machine learning models. | [Code](https://github.com/fs302/Algorithms/blob/master/LIME/lime_explainer.ipynb) |
|MiniRNN| Implement of a simple RNN on text generation and used for lyrics generation. | [Code](https://github.com/fs302/Algorithms/blob/master/miniRNN/rnn.py) |
|VAE| VAE(Variational Autoencoder) tutorial. | [Code](https://github.com/fs302/Algorithms/blob/master/VAE/VAE_PyTorch.ipynb) |
|Neural Style Transfer| Tutorial: Neual Transfer Using PyTorch. | [Code](https://github.com/fs302/Algorithms/blob/master/neural_transfer/neural_transfer_pytorch.ipynb) |
|BERT | BERT is a pre-train language model | [Doc](https://github.com/fs302/Algorithms/blob/master/BERT/README.md) |

Algorithms

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