BestPractices
jupyter-memgraph-tutorials
BestPractices | jupyter-memgraph-tutorials | |
---|---|---|
1 | 1 | |
155 | 22 | |
- | - | |
2.8 | 10.0 | |
6 months ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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BestPractices
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Ideas for Materials Science / Data Science projects
My research group recently wrote the definitive best practice guide for getting into this field. We provide a GitHub with some example data that you could take a look at. The code snippets will be really useful because we have them really well commented. https://github.com/anthony-wang/BestPractices
jupyter-memgraph-tutorials
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How to Use Memgraph With Python and Jupyter Notebooks
You will need to download this file which contains a simple dataset called Zachary's karate club. To import it into Memgraph, we will first need to copy it to the Docker container where Memgraph is running.
What are some alternatives?
nbdev - Create delightful software with Jupyter Notebooks
domaine-nc-jupyter-notebook - Jupyter Notebook dédié à la l'analyse des noms de domaines en Nouvelle-Calédonie
fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
jupyter-memgraph-tutorials - Learn to use Memgraph and GQLAlchemy quickly with the help of Jupyter Notebooks
py - Repository to store sample python programs for python learning
rust-data-analysis - Rust for data analysis encyclopedia (WIP).
pymatgen - Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
graph-notebook - Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.
reinforcement_learning_course_materials - Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
jupytemplate - Templates for jupyter notebooks
machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo