Exploiting the Power of Open Data Science for Predictive Analytics

Open Data Science is an inclusive movement that makes the open source tools of data science - data, analytics and computation – easily work together as a connected ecosystem.

However, not all open source data science tools and platforms fully embrace the open connectedness of this movement. Many existing open source technologies are isolated and lack the interoperability with the underlying operational infrastructure foundation, but that interoperability is key to success in building, sharing and deploying predictive analytics in enterprises.

Anaconda is the leading full-stack Open Data Science platform. This means Anaconda addresses difficult and complex operational problems while providing Data Science teams with the power of the latest innovations in open source analytics. Anaconda also makes it easy to collaborate across the entire Data Science team, no matter where in the world members may be located.

In this paper, you'll learn how Anaconda enables powerful predictive analytic solutions for enterprises, including:
  • Managing operational issues easily
  • Creating predictive analytic models with Python, R and Jupyter Notebooks
  • Integrating your predictive analytic models into intelligent web apps, interactive visualizations, or embedding them into any existing operational process


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About the Author

Christine Doig

Christine Doig is a Senior Data Scientist at Continuum Analytics, where she worked on MEMEX, a DARPA-funded project helping stop human trafficking. She has 5+ years of experience in analytics, operations research, and machine learning in a variety of industries, including energy, manufacturing, and banking.
Christine holds a M.S. in Industrial Engineering from the Polytechnic University of Catalonia in Barcelona. She is an open source advocate and has spoken at PyData, EuroPython, SciPy, PyCon, and many other conferences.