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100+  Past Speakers 

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TMLS Team

  • DAVID sCHARBACH, Director, founder tmls

  • Amir Feizpour, Data Scientist, Scientific Advisor, rbc

  • Tina Aprile, entrepreneur, Organizer tmls

  • April Grace de las Alas, structural coordinator, tmls

  • Diego Cantor, Ph.D, head of presentations TMLS, Founder, CTO, EZRA

  • Sean Robertson, ASSOCIATE, syntegrity

  • Amy Mansell, Organizer tmls, project manager, lighthouse labs

  • MAECY SANTOS, EA TMLS

  • Faraz thambi, maRKETING & PARTNERSHIPS

  • Maria D'Angelo, ph.d, Head of diversity & Inclusion Programs tmls, Data Scientist, delphia

  • Reena Shaw, hEAD OF EDITORIAL CONTENT TMLS, Lead data scientists, agile blockchain

  • Julia Mariglia, MANAGER TMLS NEWSLETTER

 
  • FRANK RUDZICK, 2018 TMLS CHAIRMAN. ASSOCIATE PROFESSOR, UNIVERSITY OF TORONTO, DEPARTMENT OF COMPUTER SCIENCE

 
  • Michael Guerzhoy, Senior Data Scientist, Research, and Training, St. Michael's Hospital, aSSISTANT PROFESSOR Utoronto

  • Laleh Soltan Ghoraie,
    tmls poSTER SESSION CHAIR, Machine Learning Researcher at Borealis AI, Affiliate, Vector Inst. 

  • Devinder Kumar, tmls poSTER SESSION CHAIR, ML PhD Candidate at UWaterloo & Vector Inst. | Lead AI Scientist, NextAI

  • Ali Harakeh,ML PhD Candidate at University of Toronto Institute for Aerospace Studies (UTIAS)

  • Asif Ahmed,Senior Financial Analyst, The Home Depot

  • Laila Paszti, Attorney, AI Software Engineer 

  • Lina Ismail, Managing Partner, thinki3

  • Ajinkya Kulkarni,Director, Artificial Intelligence and Machine Learning, scotiabank

  • Rupam Mahmood,
    AI Research Lead, Kindred.ai

  • Matt McInnis, Data Scientist, Customer Success Unit, Microsoft

  • Susie Pan, Product Lead, RBC Ventures

  • Jeremie Harris, Co-Founder, SharpestMinds

  • Pavan Singh, Director
    Business Intelligence & Analytics, Firmex

  • Asaf Inger,VP Engineering at BenchSci

  • Geoffrey Hunter,
    Data Science Manager at Uberflip

  • Ramy Nassar, Director, Retail innovation lab, Mattel, Inc.

  • Amir massoud Farahmand, Faculty Member at Vector Institute

  • Max Huang, Data Scientist, Cerebri AI

  • Alex Milodowski, Senior Manager, Client Analytics at Aimia Inc

  • Elham Dolatabadi,
    Machine Learning, Data Scientist, RBC

  • Catherine CheN,
    founder & ceo, IG Liaison Strategy & Business Consulting

  • Diederik van Liere,
    Director of Data Science and Engineering, Shopify,

  • Ozge Yeloglu,Chief Data Scientist, Customer Success Unit at Microsoft Canada

 

For Sponsorship availability please email info@torontomachinelearning.com

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Why attend TMLS?

Machine Learning and Artificial Intelligence are unlocking unprecedented business advantage and delivering exciting, rewarding careers. Despite the vast opportunities that lie in our data, there are also explicit challenges to harnessing them effectively.

To address these challenges and to foster 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 local members to create 4 parallel tracks over 3 days: for Business Leaders, and 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 Natural Language Processing, Neural Nets, Reinforcement Learning, Generative Adversarial Networks (GANs), Evolution Strategies, AutoML and more. 

The content will be practical, non-sponsored, and tailored to our local eco-system. TMLS is not a sales pitch - It's a connection to a deep community that is committed to advancing ML/AI to deliver value and exciting careers for Canadian Businesses and Individuals


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Attendees

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 Natural Language Processing, Neural Nets, Reinforcement Learning, Generative Adversarial Networks (GANs), Evolution Strategies, AutoML and more. 

 

Attendees from 2017-18 Events

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2018 Attendee Demographics

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2017-2018 Attendee Titles 

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Deep Community

The work we do extends both before and after the Toronto Machine Learning Summit. We bring the community together for:

  1. Toronto Machine Learning Micro-Summit's: practitioner-driven gatherings, speakers share real successes and failures in the world of Machine Learning.

  2. Toronto Deep Learning Seminar (TDLS): for advanced scientists to understand the latest advances

  3. CTO/CIO Breakfasts: for business leaders to explore their challenges in an intimate setting with experienced AI implementers

  4. Machine Learning Transition Programs: placing practitioners and PhD's on co-op projects that translate to full-time employment

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Join the Community List and newsletter

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Daniels Spectrum operates as a social enterprise with a special mandate to support culturally diverse and inclusive events.

DANIELS sPECTRUM

585 Dundas St E, Toronto, ON M5A 2B7

5 min drive from Yonge & Dundas. 20 minute walk. 10 min streetcar.

By TTC

Daniels Spectrum can be accessed via TTC by taking the 505 Dundas Streetcar to Sackville Street. You can also take the 95 Parliament Bus to Dundas Street and walk 500m east.

Parking

Paid public parking is available in the underground lot beneath Daniels Spectrum. Parking costs a flat rate of $10 per day. There is also free parking along Dundas St. West between 9am and 4pm.

 
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