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        "author": "Shivam Agarwal",
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        "description": "# Keras-training-tools \n\nImplementation of some of the very effective tools for training Deep Learning (DL) models that I came across while doing the fastai course on [Practical Deep Learning for Coders](https://course.fast.ai/). \n\nThe tools were first presented in the following papers by Leslie N. Smith:\n- LR Finder: [A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay](https://arxiv.org/abs/1803.09820)\n- One Cycle Scheduler: [Cyclical Learning Rates for Training Neural Networks](https://arxiv.org/abs/1506.01186)\n\nMy implementations are a port of the code in [fastai library](https://github.com/fastai/fastai) (originally, based on Pytorch) to Keras and are heavily inspired by some of earlier efforts in this direction:\n\n- https://github.com/surmenok/keras_lr_finder\n- https://github.com/titu1994/keras-one-cycle\n\nHere's another article I referred to: [How Do You Find A Good Learning Rate](https://sgugger.github.io/how-do-you-find-a-good-learning-rate.html) by Sylvain Gugger of fastai which provides an intuitive understanding of how fastai's LR finder works. \n\nI'll keep updating this repository with the new tools I come across that could be practically useful for training a DL model.\n\n",
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