This two day training course will provide delegates with an in-depth, theoretical and practical understanding of machine learning applications, models, and more advanced tools and solutions through a quantitative approach. The action-packed agenda will delve into a variety of main theories, current applications of machine learning and showcase some case studies. It will examine what impact machine learning has on trading, portfolio construction and optimization as well as focus on the relationship between Deep Learning and Big Data, applications of Natural Language Processing and Quantum Computing. The course is delivered by the top practitioners from the leading financial institutions working in the machine learning field, and held in an open and discussion based learning environment. URLs:Tickets: https://go.evvnt.com/411850-2?pid=5569Brochure: https://go.evvnt.com/411850-3?pid=5569 Prices:Two Day Training Course (Super Early Bird): USD 2199.0,Two Day Training Course (Super Early Bird 3 for 2): USD 1466.0,Two Day Training Course (Early Bird): USD 2399.0,Two Day Training Course (Early Bird 3 for 2): USD 1599.33,Two Day Training Course: USD 2599.0,Two Day Training Course (3 for 2): USD 1732.66,Complimentary Guest: USD 0.0,Speaker: USD 0.0,Speaker Guest: USD 0.0 Speakers: Steve Yalovitser Co-Founder, New York Quantum Computing Meet-up and Director, XVA Quant Core Lead Wells Fargo, Petter Kolm Professor And Director of the Mathematics in Finance, Courant Institute New York University, Ken Perry Former CRO OCH-ZIFF Capital Management, Terry Benzschawel Founder and Principal Benzschawel Scientific, Arik Ben Dor Head of Quantitative Equity Research BARCLAYS, Elliot Noma Machine Learning Engineer Consultant Federal Reserve Bank of New York, Patrick Dugnolle Head of Multi-Assets and Quantitative Solutions BNP Paribas Asset Management Date and Time: On Thursday June 06, 2019 at 9:00 am (ends Friday June 07, 2019 at 5:00 pm) Venue Details: 55 Broad Sreet, 55 Broad Sreet, Fl 22, Financial District, New York, NY, 10004, United States