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Data Science Virtual Machine for Linux (Ubuntu)

Virtual machine with deep learning frameworks and tools for machine learning and data science

The Data Science Virtual Machine for Linux is an Ubuntu-based virtual machine image that makes it easy to get started with deep learning on Azure. CNTK, TensorFlow, MXNet, Caffe, Caffe2, DIGITS, H2O, Keras, Theano, and Torch are built, installed, and configured so they are ready to run immediately. The NVIDIA driver, CUDA, and cuDNN are also included. All frameworks are the GPU versions but work on the CPU as well. Many sample Jupyter notebooks are included.

This Virtual Machine image is currently in preview.

The Data Science Virtual Machine for Linux also contains popular tools for data science and development activities, including:

  • Microsoft R Server 9.0 with Microsoft R Open 3.3.2
  • Anaconda Python 2.7 and 3.5
  • JupyterHub with sample notebooks
  • Apache Drill for querying non-relational data using SQL
  • Spark local 2.0.2 with PySpark and SparkR Jupyter kernels
  • Single node local Hadoop (HDFS, Yarn)
  • Azure command-line interface
  • Visual Studio Code, IntelliJ IDEA, PyCharm, Atom
  • JuliaPro, a curated distribution of Julia Language and tools
  • Vowpal Wabbit for online learning
  • xgboost for gradient boosting

You can view a full list of installed tools for the Linux edition here.