adadelta
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"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
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Jun 19, 2024 - Jupyter Notebook
Data Structures, Algorithms and Machine Learning Optimization
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Jul 31, 2023 - Jupyter Notebook
Using Densenet for image classification in PyTorch
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Dec 8, 2022 - Jupyter Notebook
Using different optimizers for a comparison study, finding the root of differences by visualization and to find the best case for a specific task
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Dec 21, 2021 - Jupyter Notebook
A tour of different optimization algorithms in PyTorch.
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Dec 11, 2021 - Jupyter Notebook
A deep learning classification program to detect the CT-scan results using python
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Sep 11, 2021 - Jupyter Notebook
Classification of data using neural networks — with back propagation (multilayer perceptron) and with counter propagation
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Aug 10, 2021 - Python
Deep Learning Optimizers
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May 29, 2021 - HTML
Coursework on global optimization methods (BGD, Adadelta)
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Mar 19, 2021 - Jupyter Notebook
Neural Networks and optimizers from scratch in NumPy, featuring newer optimizers such as DemonAdam or QHAdam.
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Feb 10, 2021 - Jupyter Notebook
Machine learning algorithm implemented from scratch in python
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Dec 28, 2020 - Python
Applied LSTM algorithm on Amazon Fine Food Review Dataset
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May 29, 2019 - Jupyter Notebook
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
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Mar 23, 2019 - Python
Clean & dependency-free implementation of the ADADELTA algorithm in python.
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Feb 10, 2019 - Python
Hands on implementation of gradient descent based optimizers in raw python
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Dec 20, 2018 - Jupyter Notebook
gradient descent optimization algorithms
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Aug 21, 2018 - Python
Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.
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Jun 21, 2018 - Jupyter Notebook
Experimenting with MNIST using the MXNet machine learning framework
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Jan 4, 2018
🔬 Nano size Theano LSTM module
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Nov 16, 2016 - Python
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