Toronto Machine Learning Society (TMLS)
David Scharbach has a diverse work experience spanning various roles and industries. David is currently working as an Organizer at Inteligencia Artificial Aplicada Latam since 2022. Before that, they served as an Executive Director at MLOps World: Machine Learning in Production, where they organized events and workshops related to the deployment of ML models in production environments. Additionally, David held the position of Executive Director at the Toronto Machine Learning Society (TMLS), where they helped strengthen the local AI/machine learning ecosystem. David also worked as an Advisor at SharpestMinds and as a Project Manager and Account Manager at KCI World. Further, David served as the Head of Strategic Partnerships at Pax Cultura Studios and as a Spanish Service Representative at Foresters. David has also held roles such as Advisory Council Member at York University and Activities Coordinator at King George International Inc. In the early stages of their career, David worked as a Program Facilitator at Junglesport Inc, where they successfully planned and executed programs for students. Overall, David has amassed valuable experience across various sectors, including artificial intelligence, machine learning, education, and customer service.
David Scharbach earned a BA double majors honors degree in Communications and Spanish from York University, where they studied from 2005 to 2010.
This person is not in any teams
Toronto Machine Learning Society (TMLS)
1 followers
TMLS is a series of deep learning seminars, bi-monthly micro-summits and a 2 day conference. TMLS is an initiative to accelerate the growth of ML/AI in Canada. We have gathered the top insights, expertise from our community of over 5,000 professionals to create a bi-monthly Toronto Machine Learning Summit (TMLS).The goal is to showcaseCanada’s research accomplishments while offering innovative solutions to real business problems faced by ML and AI practitioners.What to expect at TMLS;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.Researchers will have the opportunity to share with their peer's cutting-edge advancements in the field.Machine Learning in Canada; Machine learning, deep learning, and AI are some of the fastest growing and most exciting areas for knowledge workers - simultaneously, they are the 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.