Productionizing and Deploying Secure and Scalable Data Science Projects

Empower your data science team with one-click deployments from Anaconda Enterprise
Traditional data science project deployments typically involve complex, time-consuming processes that take data scientists away from what they do best: exploring and analyzing data. But why place this burden on your data science team when Anaconda Enterprise can handle the process instead—all with the single click of a button?

In this free whitepaper from Team Anaconda, our data science experts share:
  • The factors to consider when deploying data science projects
  • How to leverage Anaconda Project for data science encapsulation
  • The unparalleled advantages of one-click data science deployments through the power of Anaconda Enterprise

Meet Our Authors

  • Christine Doig was a Senior Data Scientist at Anaconda, where she worked on MEMEX, a DARPA-funded project helping stop human trafficking. She is the co-author of Breaking Data Science Open, published by O'Reilly. 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 an MS 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.
  • Kris Overhold is a Senior Product Manager at Anaconda, developing the cluster management features of Anaconda. He has 10+ years of experience in scientific computing, systems administration, computational modeling and more. Kris holds a Ph.D. in Civil Engineering from the University of Texas and a Master’s degree from Worcester Polytechnic Institute, focusing on computational fluid dynamics.
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