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Toronto machine learning summit

A 2-day, 1-night creative exploration of Big Data, ML, and AI in Toronto.

Join to learn more.

November  2-3  2017

TMLS is a unique event focusing on both business, and technical applied ML/AI. Throughout 2 days, TMLS will bring together Toronto's best and brightest Practitioners, Researchers, Entrepreneurs and Executives to highlight our community and foster growth in the local ecosystem.

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2 DAYS, 2 Nights, 4 TRACKS  November 2nd-3rd 2017
8:30am-10pm, 8:30am- 6pm, Daniels Spectrum 585 Dundas St E


Event TRacks
 

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Business

(Non-Technical)

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Advanced

(Technical)

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Case Studies

(Applied)

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Workshops

(Business/Technical)

 

Thanks to our Sponsors:

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TMLS 2017 Speakers

  • David Duvenaud
    Assistant Professor of Machine Learning
    University of Toronto
     
  • Ozge Yeloglu
    Chief Data Scientist,
    Microsoft Canada
     
  • Brian Keng
    Chief Data Scientist
    Rubikloud Technologies Inc.
  • Ankit Jain
    Founder at Gradient Ventures- Google’s New AI-focused Venture Fund

  • Heather Evans
    Senior Advisor, Advanced Technologies (AI/Quantum) Ontario Ministry of Economic Development and Growth
     
  • Amir Hajian
    Director of Research
    Thomson Reuters
     
  • Susie Pan
    Product Lead in AI Research, Entrepreneur
    RBC Research Institute
     
  • Rezsa (Rez) Farahani
    Director of Machine Learning
    Vevo
     
  • G Wu
    CEO of Adeptmind, Co-founder Maluuba
     
  • Christopher Srinivasa
    Machine Learning Research Team Lead
    RBC Research Institute
     
  • Anthony de Fazekas
    Partner, Lawyer, Patent Agent
    Head of Technology & Innovation, Canada
    Norton Rose Fulbright Canada
     
  • Steve Kludt
    Chief Data Scientist & CTO
    Canvass Analytics
     
  • Lindsay Farber
    Senior Data Scientist and Head of Business Intelligence Moneykey
     
  • Narbe Alexandrian
    Senior Associate
    OMERS Ventures
     
  • Yanshuai Cao
    Machine Learning Research Team Lead
    RBC Research Institute
     
  • Parinaz Sobhani
    Director of Machine Learning, Impact Team
    Georgian Partners
     
  • Jamie McDonald
    Co-Founder, Co-CEO
    Hubdoc
     
  • Steven Waslander
    Associate Professor
    University of Waterloo
     
  • Bryan Watson
    Partner
    Flow Ventures
     
  • Bala Gopalakrishnan
    Managing Director, Data Solutions
    Pelmorex Corp (The WeatherNetwork)
     
  • Ramzi Abdelmoula
    Systems engineer in speech recognition & ML specialist for Advanced Technical Work
    General Motors
     
  • Dora Jambor
    Machine Learning Engineer
    Shopify, Discovery Algorithm Engineering
     
  • Putra Manggala
    Machine Learning Engineering Lead
    Shopify,Discovery Algorithm Engineering
  • Tomi Poutanen
    CEO of Layer-6 AI, Co-Founder of Vector Institute, Fellow at Creative Destruction Lab
     
  • Tanmay Bakshi
    13-year-old author, algorithmist,
    TedX speaker and Cloud Advisor at IBM
     
  • Charumitra Pujari
    AI and Machine Learning Leader
    Paytm Labs
     
  • Eli Fathi
    CEO
    MindBridge AI
     
  • Harish Bhaskar
    Director of Artificial Intelligence & Chief Scientist
    LinKay Technologies
     
  • Devinder Kumar
    AI Scientist in Residence at NextAI, PhD Student
    Deep Learning at University of Waterloo
     
  • Pavan Singh
    Director, Information Management & Analytics
    Firmex
     
  • Dr. Annie Lee, PhD
    Lead Research Scientist
    VerticalScope Inc
     
  • Ramaneek Gill
    CTO
    YOLK Inc., Researcher UofT
     
  • Peter Varhol
    Principal
    Technology Strategy Research, LLC
     
  • Eric TK Chou, PhD
    VP of Research & Development
    Goldspot Discoveries
     
  • Yang Han
    CTO
    StackAdapt
     
  • Aidan Gomez
    Researcher
    University of Toronto, Google Brain
     
  • Mohammad Javad Shafiee
    Research Assistant Professor
    University of Waterloo
     
  • Alex Levinshtein
    Director of Computer Vision
    ModiFace Inc
     
  • Joseph Geraci
    CSO and Founder
    NetraMark Corp
     
  • Faisal Ahmed
    Chief Technical Officer
    Knockri
     
  • Geoffrey Hunter
    Data Sciences Lead
    TribalScale
     
  • Michael Guerzhoy
    Computer Science Lecturer at U of Toronto
    Data Science Consultant
     
  • Diego Cantor PhD
    Consultant
     
  • Eric Huang
    Director  
    Advanced Analytics and Research Lab
     
  • Baiju Devani
    Vice President of Analytics
    AVIVA
  • Zaynah Bhanji, 13 yrs old 

    Jerry Qu, 16 yrs old, 

    Tommy Moffat, 16 yrs old
     


See Timetable here

 

 
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Why 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 2 parallel tracks over 2 days: one for Business Leaders, and one 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 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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Deep Community

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

  1. Meetups: practitioner-driven gatherings, speakers share real successes and failures in the world of Machine Learning
  2. Special Interest Group - Deep Learning (SIG-DL): 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 practicioners and PhD's on co-op projects that translate to full-time employment
  5. Research Scholarships: for scientists to stay in Toronto and perform exciting research aligned with real business objectives

Join the Community List and newsletter - we'd love to meet face to face to hear your stories and needs

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Thank you to our sponsors

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Toronto Machine Learning Summit Organizing Team 

David Scharbach Ask me about: Local events and Ph.D  students to help with project needs.   

David Scharbach

Ask me about: Local events and Ph.D  students to help with project needs. 

 

Michael Guerzhoy Ask me about: Applied ML, computer vision, and data science education

Michael Guerzhoy

Ask me about: Applied ML, computer vision, and data science education

Maria D'Angelo, PhD Ask me about: Neural networks being used to understand human behaviour  

Maria D'Angelo, PhD

Ask me about: Neural networks being used to understand human behaviour

 

Sean Robertson Ask me about: Starting off in ML and AI, Enterprise-level Solutions

Sean Robertson

Ask me about: Starting off in ML and AI, Enterprise-level Solutions

Amir Feizpour, PhD

Ask me about: Physics and Quantum machine learning

 
Alex Glinka Ask me about: Leading innovation teams

Alex Glinka

Ask me about: Leading innovation teams

Jing Qian Ask me about: Business growth and transformation using data and technology

Jing Qian

Ask me about: Business growth and transformation using data and technology

Trang Lam Ask me about: Software development

Trang Lam

Ask me about: Software development

 
Armando Benitez Ask me about: Solving data problems at scale

Armando Benitez

Ask me about: Solving data problems at scale

Diego Cantor, PhD Ask me about: Deep learning in medical imaging, healthcare and finance

Diego Cantor, PhD

Ask me about: Deep learning in medical imaging, healthcare and finance

Steve Pereira

Ask me about: DevOps and applied AI for business

 
Reena Shaw Ask me about: ML in Finance, Data Science education

Reena Shaw

Ask me about: ML in Finance, Data Science education

In the next five years, every company is going to need an AI strategy.
— Tiff Macklem, dean of the Rotman School of Management at the University of Toronto
 
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FAQ

 

Q: Why should I attend the TMLS? 

Developments are happening fast - it's important to stay on top. 

For businesses and experts, you will have direct contact to the people that matter most. For data practitioners you'll learn how to cut through the noise and fast-track your learning process.

This event is casual, and ticket are priced as low as possible to help remove all barriers to entry. Space however is limited. Tell us your businesses's burning questions and we'll have you directly matched with the right answers, and people who can make a difference. 

Q: Who will attend? 

The event will have two tracks: One for Business, one for Practitioners.  Business exec's, PhD researchers, and practitioners ranging from Beginner to Advanced (multiple project experience). 

Q: I'm not sure artificial intelligence can benefit my business. Is this still relevant? 

Yes, Describe to us your project or problems and we will connect you with researchers and council, on site. No additional charges. 

Q: Can my company have a display? 

Yes, there will spaces for company displays. You can inquire at info@torontomachinelearning.com.

Q: Will tickets include access to the after-party? 

Yes, attendees will have full access to the post event networking social. 

Q: Where and how can I register?

Visit here to reserve your spot. 

Q: Will you give out the attendee list? 

No, we do our best to ensure attendees are not inundated with messages, We allow attendees to stay in contact through our slack channel and follow-up monthly socials,

Q: Can I speak at the event?

Yes you can submit an abstract here. Deadline to submit a talk is Sept 20th. 

*Content is non-commercial and speaking spots cannot be purchased. 

Q: What's the date, time? 

Thursday November 2nd, 9am-10pm (including after-party) Friday November 3rd, 9am- 5pm (Relocate to local pub afterwards). 

Q: Where is the event taking place? 

The event will take place at Daniels Spectrum, 585 Dundas Street East Toronto, On M5A 2B7. See more information about the venue here.  

Q: Do you have a hotel block or discounts?

We do not have hotel discounts. 

Q: Who can I speak with for questions? 

You can visit here for more information, or email info@torontomachinelearning.com and somebody will be in contact within 24 hours. 

 

TMLS Code of Conduct