Here is a list of demonstrations and tutorials.
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Tips and Tricks: Just a few simple and helpful tips.
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VIP CheatSheets contain several pfd files covering AI/ML/DL/ODE/Probabilitiy and Statistics.
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jupyter lab: An alternative to jupyter notebook.
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Using GPU on macOS with M-chip is way faster than running on CPU.
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GPU Servers: Here is how you can run Python on one of our GPU machines.
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/q-learning/contains a PyTorch implementation of Q-learning with vectorizedgymenvironments. It also contains a presentation summarizing the mathematics behind deep Q-learning. See Mnih et al (2015). Author: Alexander Van de Kleut. -
Pandas Essentials: There are three files introduced differnet aspect of Pandas.
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/learn-git/contains reference materials for common git and github workflows. Author: Alexander Van de Kleut. -
/tensorboard/contains a demonstration of TensorBoard, a framework for saving and visualizing results from experiments. Author: Haris Zahid -
Hyperparameter search using NNI: You can download and try this simple example, and build from there.
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Webpage starter: Initial steps to build a personal website. open the file in sublime or other similar editors.
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Policy Gradient: Alex taught us about policy gradient, and REINFORCE.
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Library includes usefull links to materials from background readings to implementations.
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Unit testing, by Brian Cechmanek and Eva Kryoneriti