netsci-labs
reinforcement_learning_course_materials
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| netsci-labs | reinforcement_learning_course_materials | |
|---|---|---|
| 1 | 1 | |
| 13 | 900 | |
| - | 0.8% | |
| 6.1 | 8.3 | |
| 2 months ago | 13 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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netsci-labs
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My network science / ML on graphs notebooks
A huge inspiration is the Stanford's cs224w course. The notebooks are structured for teaching. https://github.com/zademn/netsci-labs
reinforcement_learning_course_materials
What are some alternatives?
QuickQanava - :link: C++17 network / graph visualization library - Qt6 / QML node editor.
ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.
graphein - Protein Graph Library
learn-monogame.github.io - Documentation to learn MonoGame from the ground up.
egsis - EGSIS: Exploratory Graph-based Semi-supervised Image Segmentation
BestPractices - Things that you should (and should not) do in your Materials Informatics research.
awesome-network-analysis - A curated list of awesome network analysis resources.
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
LlamaIndex-course - Learn to build and deploy AI apps.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
gds_env - A containerised platform for Geographic Data Science
JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.