This event will be Livestreamed here:
https://livestream.com/accounts/23925505/events/8591462/edit
Since the release of Julia 1.0 last August, Julia has continued to pick up steam for technical computing applications. We'll see some reasons you should care about the language that "walks like Python, runs like C", including:
- Ease of programming
- Use in Jupyter notebooks
- Data manipulation libraries
- Easy connection to sklearn & other Python libraries
- State of the art libraries for constrained optimization, differential equations, & machine learning
- Powerful extensibility
And more!
Chad enjoys that data science gives practical approximations to the complex uncertainties of reality.
Chad comes to Metis from a diverse technical background. After earning his mathematics PhD from Indiana University, Chad joined Pacific Northwest National Laboratory to work on statistical & computational challenges ranging from homeland security to high-performance computing & machine learning research. Following several of his publications at top-tier ML conferences, he turned to probabilistic programming, then still in its infancy. He has used these systems for consulting projects for industrial clients, & has led development & publication of several new ones along the way. In his spare time, Chad enjoys a wide range of music, & practices martial arts, where he has black belts in several styles.
About Metis
Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, & corporate programs based in Seattle, New York, Chicago, & San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, & more. Students & alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.
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http://bit.ly/MetisCommunitySlack
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