Displaying 1 to 20 from 21 results

numpy-100 - 100 numpy exercises (100% complete)

  •    Jupyter

This is a collection of numpy exercises from numpy mailing list, stack overflow, and numpy documentation. I've also created some problems myself to reach the 100 limit. The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercises for those who teach. This work is licensed under the MIT license.

binderhub - Deterministically build docker images from a git repository + commit

  •    Python

BinderHub allows you to BUILD and REGISTER a Docker image using a GitHub repository, then CONNECT with JupyterHub, allowing you to create a public IP address that allows users to interact with the code and environment within a live JupyterHub instance. You can select a specific branch name, commit, or tag to serve. BinderHub is created using Python, kubernetes, tornado, and traitlets. As such, it should be a familiar technical foundation for Jupyter developers.


  •    CSharp

Xml Object Mapper is a framework for transforming .NET objects from/to XML.

AgentNet - Deep Reinforcement Learning library for humans

  •    Python

AgentNet is a deep reinforcement learning framework, which is designed for ease of research and prototyping of Deep Learning models for Markov Decision Processes. We have a full in-and-out support for Lasagne deep learning library, granting you access to all convolutions, maxouts, poolings, dropouts, etc. etc. etc.

talk-python-intro - Introduction to Python (Jupyter based)

  •    Jupyter

July 20 2017 update: mybinder seems to be down and one needs to use the beta version.

ScientificComputingForTheRestOfUs - Introduction to Scientific Computing 🦊

  •    Jupyter

One specific challenge, when writing code as a scientist, is that we care a lot about getting the right answer; but of course, the right answer is not always obvious. So we should be very careful with the code we write. A piece of code that crashes is annoying; but a piece of code that runs, and give you the wrong answer can compromise your science and your career. This guide will help you adopt practices that make it less likely to introduce mistakes in your code, and more likely to catch them. Hopefully, this will let all of us write code we can trust more. Good principles in scientific computing can help you write code that is easier to maintain, easier to reproduce, and easier to debug. But it can be difficult to find an introduction to get you started. The goal of this project is to provide reproducible documents you can use to get started on the most important points. You can use these lessons on your own, or as a group.

reactx - A React.js Extension Library, add missing features form React.js

  •    Javascript

Install using npm. ReactX is designed to be fully backward compatible with React, which can be used as drop in replacement of React without any code change.

python-audio - Some Jupyter notebooks about audio signal processing with Python

  •    Jupyter

This repository holds a few Jupyter (formerly known as IPython) notebooks. The authors waive copyright and related rights in the work through the CC0 1.0 Universal public domain dedication.

CSC_deeplearning - 3-day dive into deep learning at csc

  •    Jupyter

Crash-course deep learning in 3 days. Lectures and corresponding seminars are in the ./day* folders.

iz - nogc: streams, containers; rtti: properties, serializer, binder; reasonable and crazy things;

  •    D

iz is a general purpose library for the D programming language. It includes streams, containers, a serializer, property binder, Pascal-like sets, Pascal-like properties and more. This library experiments manually managed lifetime. Most of the classes declared in iz are not compatible with new and destroy, instead construct and destruct must be used.

openrefineder - 💠 + 📚 OpenRefine on Binder!

  •    Python

To access OpenRefine wait for the binder to launch. Then click "New -> OpenRefine session" on the right hand side of the screen. A new tab should open which after a few seconds will show the familiar OpenRefine home screen.

binder - Binder metapackage for usage, docs, and chat


This repository contains the documentation and usage instructions for the mybinder.org service. For deployment of the website mybinder.org, please visit mybinder.org-deploy.

helm-chart - A store of Helm chart tarballs for deploying JupyterHub and BinderHub on a Kubernetes cluster


This repository stores Helm chart tarballs for BinderHub and JupyterHub. While this repo is a store of Helm chart tarballs, actual development of the Helm charts takes place in the BinderHub and Zero to JupyterHub repos. These Helm charts are used with Kubernetes deployments of BinderHub and JupyterHub. The gh-pages branch of this repo contains the latest helm charts for BinderHub and JupyterHub. It also contains historical charts as well.

mybinder.org-deploy - Deployment config files for mybinder.org

  •    Jupyter

Deployment, configuration, and Site Reliability documentation files for the public mybinder.org service. These files are specific to mybinder.org. If you wish to deploy your own Binder instance, please do not use these files. Instead, you should review the BinderHub documentation and the jupyterhub/binderhub repo to set up your deployment.

team-compass - A repository for team interaction, syncing, and handling meeting notes across the JupyterHub ecosystem

  •    Jupyter

The currently-active team report exists in a HackMD. Each week, team reports are archived in the weekly reports archive. Then, a new report is created with the team report template. The list of "core" members of the JupyterHub and Binder projects can be found on the team-compass website.

examples - Example nteract notebooks with links to execution on mybinder.org

  •    Jupyter

Go ahead and give these notebooks a try. This repository has collections of nteract notebooks to try out on Binder. Click the link of an individual example or the language heading for a bundle of notebooks.

quickviz - Visualize a pandas dataframe in a few clicks

  •    Jupyter

Quickviz provides widgets for quickly visualizing pandas dataframes. It interfaces with seaborn and pandas.plot. See the gallery (which is also a test suite) for more.

juniper - 🍇 Edit and execute code snippets in the browser using Jupyter kernels

  •    Javascript

Juniper is a lightweight JavaScript library for adding interactive, editable and runnable code snippets to any website. It uses JupyterLab components and Binder (or your own self-hosted version of BinderHub) to launch Python, R or Julia environments based on a GitHub repository and an auto-built Jupyter-enabled Docker image. This project was heavily inspired by Min RK's Thebelab package – thanks for the great work on this. It was also instrumental in helping me understand how JupyterLab works under the hood. Also thanks to Binder for making their great service available and allowing such a smooth integration.

Binder - 🦁"Hello World" <-> [🏷, 🏷, 🏷, 🏷]

  •    Swift

A lightweight data binding for components on iOS, easy to use and does not have retain cycle. Binder is released under the MIT license. See LICENSE for details.