By David Smith
A new member has just joined the family of Data Science Virtual Machines on Azure: The Deep Learning Virtual Machine. Like other DSVMs in the family, the Deep Learning VM is a pre-configured environment with all the tools you need for data science and AI development pre-installed. The Deep Learning VM is designed specifically for GPU-enabled instances, and comes with a complete suite of deep learning frameworks including Tensorflow, PyTorch, MXNet, Caffe2 and CNTK. It also comes witth example scripts and data sets to get you started on deep learning and AI problems, including:
- Jupyter notebooks to compare performance and accuract of deep learning frameworks;
- A how-to guide for building an object recognition system using deep learning;
- Data and scripts to build a LSTM-based hierarchical attention network to classify Amazon reviews;
- Unstructured text analytics with Biomedical entity extraction.
The DLVM along with all the DSVMs also provides a complete suite of data science tools including R, Python, Spark, and much more:
There have also been some updates and additions to the tools provided in the entire DSVM family, including:
- The new Azure Machine Learning Workbench (currently in preview, and available as a one-click install from the deployed instance);
- The MMLSpark machine learning library, and the ability to run MMLSpark on a local Spark standalone instance;
- H2O Deep Water and Sparkling Water (on Ubuntu only);
- The PyCharm Python IDE (on Windows only).
All Data Science Virtual Machines, including the Deep Learning Virtual Machine, are available as Windows and Ubuntu Linux instances, and are free of any software charges: pay only for the infrastructure charge according to the power and size of the instance you choose. An Azure account is required, but you can get started with $200 in free Azure credits here.
Microsoft Azure: Data Science Virtual Machines
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