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 jupyterhubIPython 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 replThe 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 syncBy 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 appPlease refer to the official docs at kubeflow.org. Please refer to the Community page.
ml kubernetes minikube tensorflow notebook jupyterhub google-kubernetes-engineSome 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 cnnPaperwork 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 dockernteract 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 analysisA web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
notebook analytics data-visualization data-analytics data-discovery data-scienceThe Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. It supports over 40 programming languages.
notebook analytics data-visualization data-analytics data-discovery data-scienceSparkmagic is a set of tools for interactively working with remote Spark clusters through Livy, a Spark REST server, in Jupyter notebooks. The Sparkmagic project includes a set of magics for interactively running Spark code in multiple languages, as well as some kernels that you can use to turn Jupyter into an integrated Spark environment. There are two ways to use sparkmagic. Head over to the examples section for a demonstration on how to use both models of execution.
spark kernel cluster livy magic sql-query pandas-dataframe jupyter pyspark kerberos notebook jupyter-notebookThese series of tutorials on Data Science engineering will try to compare how different concepts in the discipline can be implemented in the two dominant ecosystems nowadays: R and Python. We will do this from a neutral point of view. Our opinion is that each environment has good and bad things, and any data scientist should know how to use both in order to be as prepared as posible for job market or to start personal project.
data-science data-science-engineering tutorial data-frame exploratory-data-analysis r jupyter notebook machine-learning
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