NOTE: Please sign-in at the registration area at the entrance. Thank you!
This will be a brief overview of the ML: Algorithms & Applications course that Sergey Fogelson will be teaching starting August 8th. He will do a live "teach" of a bit of the first ML class, going over a comparison of linear vs. non-linear classification algorithms. At the end, Sergey will then take any questions from event attendees about the course.There will be a cap of 30 people at this course to maintain instruction quality.
Want to learn more? Enroll in his upcoming courses here.
What to Know & Bring
Some knowledge of Python for data science will be expected.A laptop & charger (for note-taking or to run some code as we walk through the libraries).
Ideally, please have the following installed:
-Python 2.7 or 3.5-Git (should be okay if you have a Mac)-Anaconda for Jupyter Notebooks(should take care of everything)
About the Instructor
Sergey Fogelsonis the vice president of analytics & measurement sciences at Viacom. He began his career as an academic at Dartmouth College in Hanover, New Hampshire, where he researched the neural bases of visual category learning & obtained his Ph.D. in Cognitive Neuroscience.
After leaving academia, Sergey got into the rapidly growing startup scene in the NYC metro area, where he has worked as a data scientist in alternative energy analytics, digital advertising, cybersecurity, finance, & media. He is heavily involved in the NYC-area teaching community & has taught courses at various bootcamps, & has been a volunteer teacher in computer science through TEALSK12.
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.
Powered 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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