PyCon 2017 Workshop, Portland OR
This builds on a great blog post by the Anaconda product managers from March 2017:
Data Science Project Encapsulation and Deployment
Anaconda provides a rich foundation of Python and R packages for data science. This tutorial will demonstrate how Anaconda can be used to turn simple models, scripts, or Jupyter notebooks into deployable applications. Participants should have Anaconda installed and have basic Python programming experience. We'll make use of machine learning and AI libraries such as Pandas, Scikit-learn, Tensorflow, and Keras. The tutorial will also demonstrate the app deployment capabilities of Anaconda Cloud.
Ian Stokes-Rees [email protected]
- Twitter: @ijstokes
- About.Me: http://about.me/ijstokes
- LinkedIn: http://linkedin.com/in/ijstokes
This presentation:
- Anaconda Cloud: https://anaconda.org/ijstokes/data-science-apps-with-anaconda/notebook
- GitHub: https://github.com/ijstokes/pycon2017-anaconda-project-data-science-apps
The material is based on the BSD-3 open source Anaconda Project, which is included in the Anaconda Distribution: