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Toronto Machine Learning Summit
November 2, 2017 @ 9:00 am - November 3, 2017 @ 10:30 pm$67 – $147
The Toronto Machine Learning Summit is a 2-day event designed to address the challenges to successfully implementing machine learning and AI in the business world, including the unique roadblocks and the innovative solutions to real problems faced by ML and AI practitioners and teams.
Machine learning, deep learning, and AI are some of the fastest growing and most exciting areas for knowledge workers – simultaneously, they are they key to untapped revenue sources and strategic insights for businesses. Firms are using AI to create unprecedented business advantages that are reshaping the global – but more specifically Canadian – economic landscape. Practitioners are leveraging and expanding their expertise to become high-impact global leaders.
Despite the vast opportunities that lie within our data, there are also explicit challenges to revealing their potential. Furthermore, transitioning to a career in practicing AL/ML, or managing ML and AI-driven businesses, are less than straightforward.
To address these challenges and to accelerate the growth of ML/AI in Toronto we have gathered the top insights, expertise and do’s-and-don’ts from our community of over 6,000 Toronto-based professionals to create the inaugural Toronto Machine Learning Summit (TMLS). The summit comprises 2 parallel tracks over 2 days: One for Businesses, andone for Practitioners.
Business Leaders, including C-level executives and non-tech leaders, will explore immediate opportunities, and define clear next steps for building their business advantage around their data.
Practitioners will dissect technical approaches, case studies, tools, and techniques to explore challenges within Natural Language Processing, Neural Nets, Reinforcement Learning, Generative Adversarial Networks (GANs), Evolution Strategies, AutoML and more.
Why should I attend the TMLS?
Developments in the field are happening fast – for practitioners, it’s important to stay on top of the latest advances. Business leaders know that implementation of new technology brings specific challenges.
The goal of TMLS is to empower practitioners and business leaders with direct contact to the people that matter most. For data practitioners you’ll hear how to cut through the noise to the innovative solutions to technical challenges. Business leaders will learn from the experience of those who have successfully implemented ML/AI and actively manage data teams.
The content will be practical, non-sponsored, and tailored to our local ecosystem. TMLS is not a sales pitch – It’s a connection to a deep community that is committed to advancing ML/AI and to create and deliver value and exciting careers for Canadian Businesses and Individuals.
We’re committed to helping you get the most out of the TMLS. Connect with us and share your business’s (and data team’s) burning questions and we’ll make sure you get the right answers from the people who can make the difference – on-site.
Joining together under one roof will be:
Machine Learning/deep learning PhDs and researchers
C-level business leaders
Enterprise innovation labs seeking to grow their teams
Community and university machine learning groups
Each ticket will give access to the entire portfolio of:
Real case studies
High-level and granular discussions
Ample networking opportunities
Tailored post-event gatherings, and
Community follow-ups through a social channel.
This event is not a black tie affair and tickets are priced accordingly – however, space will be limited. Register now.
We ask that you direct any questions, requests to speak, requests for a Sponsorship Prospectus, etc. to email@example.com.
We’re very excited to see you there!
-The TMLS Team
The TMLS community helps promote the development of AI/ML by helping data practitioners fast-track their learning process, and businesses gain direct contact to the people who matter most.
Event site: www.torontomachinelearning.com
Submit an abstract (Talk Submissions): https://torontomachinelearning.com/speak/