Toronto Machine Learning Society (TMLS)
Abdul Rahman Sattar is an accomplished AI and Cybersecurity leader with a wealth of experience across various organizations. Currently, Sattar serves as an AI & Cybersecurity Leader at Traxese Inc. and as Co-Chair at the Cloud Security Alliance, leading research at the intersection of DevSecOps, MLOps, AIOps, and Zero Trust Security. Sattar also holds the position of Lead for Zero Trust Architecture at the National Institute of Standards and Technology (NIST) focusing on Multi-Cloud Security. Additionally, Sattar is an Entrepreneur in Residence at the Rogers Cybersecure Catalyst and plays a significant role as a conference chair, panelist, and speaker at multiple international forums. With a background in automotive cybersecurity as the Toronto Chapter Lead for the Automotive Security Research Group and a distinguished scientist role at Arctic Wolf, Sattar demonstrates profound expertise in cybersecurity analytics. Sattar earned a Bachelor of Applied Science in Computer Engineering from the University of Toronto.
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Toronto Machine Learning Society (TMLS)
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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.