Introduction to Conda for (Data) Scientists Tutorial | SciPy 2020 | David Pugh

This tutorial is a Software Carpentry-style introduction to Conda for (data) scientists.

Conda is an open source package and environment management system that runs on Windows, macOS and Linux. Conda installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. While Conda was created for Python programs it can package and distribute software for any languages such as R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN.

This tutorial motivates the use of Conda as a development tool for building and sharing project specific software environments that facilitate reproducible (data) science workflows. Particular attention is given to using Conda to create reproducible environments with NVIDIA GPU dependencies (including environments for Horovod, TensorFlow, PyTorch, and NVIDIA RAPIDS) as well as a discussion of best practices for using Conda in HPC environments.

Find additional information and set up instructions for the SciPy 2020 Tutorials at https://www.scipy2020.scipy.org/tutorial-information

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