Data Science Dojo delivers data science education, consulting, and technical services to harvest the power of data.

Trademarks: This software listing is packaged by Data Science Dojo. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

JupyterHub gives you an effortless coding environment in the cloud and is your ideal companion for diving into the world of programming. The service has built-in support for programming languages: R, Python and Bash, that are popular in data science, machine learning, and deep learning. You can integrate your programming code along with outputs, narrations, multimedia into one single document. Users can work easily on Microsoft cloud services without burdening themselves with installation and maintenance tasks. Moreover, the responsiveness and processing speed are intensified as the computations are not performed locally on your system, but up in the cloud!

• Teams of developers
• Data scientists
• Machine learning engineers
• Scientific researchers' group
• And anyone else interested in data science tools

• Pre-installed packages: 
  1. This VM (Virtual Machine) has several popular tools for data exploration, analysis, modeling & development pre-installed.
• Client-kernel decoupling: 
  1. The kernel is separate from the front-end. Our VM contains both R and Python kernels.
• Interactive environment:   
  1. With our virtual machine image, you can analyze data, visualize it, and construct machine learning models in Python and R. 
• Ease of customizability: 
  1. The notebook interface allows you to customize your experience. It is possible to change everything from the theme to the behavior of individual cells and widgets.
• Easy Conversion: 
  1. The Jupyter includes a unique tool called nbconvert that converts notebooks to HTML and PDF. nbviewer, another online tool, lets us see a publicly available notebook in the browser.
• Custom Magic Commands: 
  1. Although the notebook in this VM includes many magic commands, you can also easily add specific functionality to new magic commands if needed.

• Minimum VM requirements:
  1. 2 CPU, 4 GB Memory
• Operating System: 
  1. Ubuntu 18.04
• Authoring Tools:
  1. Jupyter, Jupyter Lab, and Terminal
• Programming Languages: 
  1. R, Python, Bash
• Python Libraries: 
  1. numpy, scipy, matplotlib, pandas, scikit-learn, seaborn, beautifulsoup4, plotly, opencv-python, azure-storage-blob, azure-storage-file, azure-storage-queue, azure-storage-common
• R Libraries: 
  1. tm, lsa, stats, miscTools, animation, lattice, rpart, party, randomForest, bst, AUC, pROC, e1071, kLaR, ElemStatLearn, glmnet, Metrics, fpc, ggplot2, caret, GGally,rpart.plot, xgboost, quanteda, plyr,dplyr, stringr, irlba, doSNOW, Rtsne, 

Users can access the VM via Remote Desktop, SSH, or browser (e.g., Jupyter Hub). Built on the Littlest JupyterHub, allowing 1-100 users on a single machine. Users have full access to this VM.