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Kutils
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Utility functions for Keras.
Download README (.md)
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README.md
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Kutils
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Download (.md)
Kutils ========== Utility functions for Keras. ### [Callbacks](https://github.com/ishank26/Kutils/blob/master/callbacks/helper.py) * **Exp_decay learning rate:** Exponential decay of learning rate w.r.t loss, after n epochs. * **Decay learning rate:** Anneal learning at end of nth epoch by custom value. * **Learning rate printer.** * **Training metrics logger.** * **Get activations of nth layer.** ### Image * **Preprocessing** * [Random rotate, Random shift (Data augmentation)](https://github.com/ishank26/Kutils/blob/master/img/preprocess/data_augment.py) * [Affine transform](https://github.com/ishank26/Kutils/blob/master/img/preprocess/data_augment.py) * [Face alignment](https://github.com/ishank26/Kutils/blob/master/img/preprocess/face_align2.py) * **Read data** * [Output data](https://github.com/ishank26/Kutils/blob/master/img/read_data/div_data.py) * [Label to txt](https://github.com/ishank26/Kutils/blob/master/img/preprocess/label.py) * [Shuffle data](https://github.com/ishank26/Kutils/blob/master/img/read_data/div_data.py) ### NLP * [**everything2vec:**](https://github.com/ishank26/Kutils/blob/master/nlp/every2vec.py) A library to integrate word2vec and data processing functions. ### Models * [**feature-SVM:**](https://github.com/ishank26/Kutils/blob/master/models/activ_cnn.py) Apply SVM to nth layer activations. ### Hyper_params Optimization * [**skopt:**](https://github.com/ishank26/Kutils/blob/master/param_op/skopt.py) Apply GridSearch, RandomSearch using sklearn. (Not working for RNN) * [**hypopt:**](https://github.com/ishank26/Kutils/blob/master/param_op/hypopt.py) Apply GridSearch, RandomSearch using hyperas library. **Note:** Repo under development. Mail me for any info or contribute :)
