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Nasratullah-Shafiq / repository
By using Jupyter Notebook we perform future employee description for succinctly outline the ideal candidate's key traits, skills, and alignment with the organization's goals.
Selected from shared topics, language and repository description—not editorial ratings.
qiskit-community /
A collection of Jupyter notebooks developed by the community showing how to use Qiskit
unskript /
Cloud-ops automation runbooks that are ready to use. Build your own automations using the hundreds of drag and drop actions included in the repository. Built on Jupyter Notebooks, our automation platform jumpstarts your SRE RunBook creation. 😎 published by the unSkript community.
janblechschmidt /
This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means of neural networks using TensorFlow.
PacktPublishing /
Practical Data Analysis using Jupyter Notebook, published by Packt Publishing
snowch /
This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop).
KMFleischer /
The PyEarthScience repository created by DKRZ (German Climate Computing Center) provides Python scripts and Jupyter notebooks in particular for scientific data processing and visualization used in climate science. It contains scripts for visualization, I/O, and analysis using PyNGL, PyNIO, xarray, cfgrib, xesmf, cartopy, and others.