Course: RegML 2020

I attented the course Regularization Methods for Machine Learning (RegML 2020). Topics: Regularization Methods: Penalization, Projection, Early Stopping. Kernel Methods Regularization in Multi-Task Learning Sparsity Geometric Deep Learning Representation Learning Here you can find my notes about the lessons. There can be errors, imprecisions and so... [Read More]
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Machine Learning Notes

.PDF Web Version Here I share a brief summary of the theory behind Machine Learning. These notes were taken during my M.Sc. (2016/2017) following the Machine Learning lectures. They might contain errors, they can be imprecise,... [Read More]
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AshPy

AshPy is a TensorFlow 2.0 library for (distributed) training, evaluation, model selection, and fast prototyping. It is designed to ease the burden of setting up all the nuances of the architectures built to train complex custom deep learning models. AshPy, why? Ashpy provides already prepared trainers for classifier... [Read More]
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