Interactive JavaScript notebooks with clever graphing.You can view a sample notebook here.
notebookThe Kubeflow project is dedicated to making machine learning on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to train, test, and deploy best-of-breed open-source predictive models to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run KubeFlow.This document details the steps needed to run the Kubeflow project in any environment in which Kubernetes runs.
ml kubernetes minikube tensorflow notebook jupyterhub google-kubernetes-engineGorilla is a rich REPL for Clojure in the notebook style. If you're interested you should take a look at its website.Contributions, in the form of comments, criticism, bug reports, or code are all very welcome :-) If you've got an idea for a big change drop me an email so we can coordinate work.
repl notebookThis is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, from basic to advanced, by using the Python language. If Python is not your language, and it is R, you may want to have a look at our R on Apache Spark (SparkR) notebooks instead. Additionally, if your are interested in being introduced to some basic Data Science Engineering, you might find these series of tutorials interesting. There we explain different concepts and applications using Python and R.
spark pyspark data-analysis mllib ipython-notebook notebook ipython data-science machine-learning big-data bigdataThis 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.
numpy binder notebook exercisesFile system notes is modern notational velocity (nvALT) on steroids. Our application respect open formats: plain/text, markdown, rtf, and stores data in file system. You can view, edit, copy data in favourite external editor and see live result in FSNotes.
notebook note-taking notes-app iosBeakerX is a collection of JVM kernels and interactive widgets for plotting, tables, autotranslation, and other extensions to Jupyter Notebook. BeakerX is in beta and under active development. The documentation consists of tutorial notebooks on GitHub. You can try it in the cloud for free with Binder. And here is the cheatsheet.
jupyter notebook sql kotlinJupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools. The two examples below may help you get started if you have Docker installed know which Docker image you want to use, and want to launch a single Jupyter Notebook server in a container.
notebook jupyter docker jupyterhubnteract is first and foremost a dynamic tool to give you flexibility when writing code, exploring data, and authoring text to share insights about the data. Edit code, write prose, and visualize.
notebook nteract data-science repl ipython jupyter jupyter-notebook desktop-application react react-components zeromq monorepo electron dataGeoNotebook is an application that provides client/server environment with interactive visualization and analysis capabilities using Jupyter, GeoJS and other open source tools. Jointly developed by Kitware and NASA Ames. Documentation for GeoNotebook can be found at http://geonotebook.readthedocs.io.
notebook mapnik jupyter jupyter-notebook-extension tile-server opengeoscience analysisThe latest version of Yosoro for macOS, linux and Windows is available here. macOS 10.9+, Windows 7+ & Linux are supported.
electron react redux notebook onedrive cloud-drive markdown antd syncIPython provides a rich toolkit to help you make the most of using Python interactively. It provides a Jupyter kernel to work with Python code in Jupyter notebooks and other interactive frontends.
interpreter python-interpreter curses terminal jupyter data-science notebook replBy utilizing a simple and minimal usage syntax, that requires a flat learning curve, taskbook enables you to effectively manage your tasks and notes across multiple boards from within your terminal. All data are written atomically to the storage in order to prevent corruptions, and are never shared with anyone or anything. Deleted items are automatically archived and can be inspected or restored at any moment. Read this document in: 简体中文, Русский.
task todo board note cli notebook command line console appSome examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py). MNIST is a database of handwritten digits, for a quick description of that dataset, you can check this notebook.
recurrent-neural-networks convolutional-neural-networks deep-learning-tutorial tensorflow tensorlayer keras deep-reinforcement-learning tensorflow-tutorials deep-learning machine-learning notebook autoencoder multi-layer-perceptron reinforcement-learning tflearn neural-networks neural-network neural-machine-translation nlp cnnBy utilizing a simple and minimal usage syntax, that requires a flat learning curve, taskbook enables you to effectively manage your tasks and notes across multiple boards from within your terminal. All data are written atomically to the storage in order to prevent corruptions, and are never shared with anyone or anything. Deleted items are automatically archived and can be inspected or restored at any moment. Read this document in: 简体中文, Русский, Français.
task todo board note cli notebook command line console appNodebook is an in-browser REPL supporting many programming languages. Code's on the left, Console's on the right. Click "Run" or press Ctrl+Enter or Cmd+Enter to run your code. Code is automatically persisted on the file system. You can also use Nodebook directly on the command line, running your notebooks upon change.
repl nodejs cpp haskell r typescript elixir ocaml fsharp notebookThe Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Kubeflow is a platform for data scientists who want to build and experiment with ML pipelines. Kubeflow is also for ML engineers and operational teams who want to deploy ML systems to various environments for development, testing, and production-level serving.
ml kubernetes minikube tensorflow notebook jupyterhub google-kubernetes-engine machine-learningPaperwork is an open-source, self-hosted alternative to services like Evernote ®, Microsoft OneNote ® or Google Keep ®. This branch contains the second iteration of Paperwork, which is a complete rewrite. Not only is it based on another framework - it is based on a completely different technology stack. It is in its very early development phase and not yet usable.
paperwork evernote opensource privacy microsoft-onenote google-keep notes notebook archive documents scylladb kong nginx nodejs dockerThe Spark Notebook is the open source notebook aimed at enterprise environments, providing Data Scientists and Data Engineers with an interactive web-based editor that can combine Scala code, SQL queries, Markup and JavaScript in a collaborative manner to explore, analyse and learn from massive data sets. The Spark Notebook allows performing reproducible analysis with Scala, Apache Spark and the Big Data ecosystem.
data-science reactive spark apache-spark notebook《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
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