To open Jupyter notebook, open a command line and run jupyter notebook. Jupyter Lab by running jupyter lab from a command line. To open Jupyter Lab, open Jupyter from the application menu or click on the desktop icon. The DSVM also comes with Jupyter, an environment to share code and analysis. To see the full list of installed environments, run conda env list in a commandline. The DSVM has multiple Python environments pre-installed, whereby the Python version is either Python 3.8 or Python 3.6. TensorFlow is available in the p圓8_tensorflow conda environment. If your machine has a GPU built in, it can make use of that GPU toĪccelerate the deep learning. Numerical computation using data flow graphs. TensorFlow is Google's deep learning library. Sample notebooks are also available in JupyterHub. You can access the Flow web UI by browsing to to get started. There are various command-line options that you might want to configure. To open H2O from the command line, run java -jar /dsvm/tools/h2o/current/h2o.jar. A Python package is installed in both the root and p圓5 Anaconda environments. H2O is a fast, in-memory, distributed machine learning and predictive analytics platform. If your machine has a GPU built in, it can make use of that GPU to accelerate the deep learning.PyTorch isĪvailable in the p圓8_pytorch environment. PyTorch is a popular scientific computing framework with wide support for machine learningĪlgorithms. See below for a list of available tools on your Ubuntu Data Science Virtual Machine.
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