Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
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Updated
Jan 6, 2022 - Python
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
A comparison between implementations of different gradient-based optimization algorithms (Gradient Descent, Adam, Adamax, Nadam, Amsgrad). The comparison was made on some of the most common functions used for testing optimization algorithms.
This project focuses on land use and land cover classification using Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The classification task aims to predict the category of land based on satellite or aerial images.
Фреймворк глубоко обучения на Numpy, написанный с целью изучения того, как все работает под "капотом".
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