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Call for Presentations:
Toronto Machine Learning Summit & Expo 2019

TMLS 2019 will be from November 20th-22nd, 2019. The call for presentation is open until September 15th, 2019.

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  • Call for Presenters (Open June 5th- closes September 15th)

  • Conference Dates:

    • Wed-NOV 20th 9am–9pm ( bonus workshop day- optional)

    • Thurs-Nov 21st 9am–5pm

    • Friday-Nov 22nd 9am–5pm

  • Attendance 1,800 people

  • Location, The Carlu Downtown Toronto.

  • *Official Media Partner Towards Data Science, which will host the video content to global audience of 10MM+


 
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#TMLS2019 is proudly partnered with Towards Data Science (TDS), one of the largest global Data Science websites and sources of written content (10MM monthly viewers). TMLS speakers will have the option to broadcast their talks on the Towards Data Science page, on a dedicated video tab, as well as include written content, accompanying their talk for TDS readers. (optional)

 
 

Suggested Themes and Topics (not limited to)

Non-Technical Talks:

Theme: Awareness, exploration and research:

  • Getting educated: Exploring where the opportunities lay

  • Creating a data strategy

Theme: Building a case for AI investment

  • Making a R.O.I case

Theme: Operational

  • Implementing AI Technology

  • Change Management and new mindsets

  • Fitting AI into the business work-flow

Workshops:

Theme: Tools

Theme: Products

Theme: Languages

Theme: Techniques

Theme: Deep Learning and NLP

And more!

Applied Technical Talks:

Theme: Strategy: matching problem with solution

  • Data collection

Theme: Dataset preparation and preprocessing

  • Data processing

  • Data anonymization

  • Legacy Technologies

  • Accessing data quality : When to start, when to get more data?

Theme: Data Splitting/Modeling

  • Overcoming data privacy and security issues

  • Small data problems

  • Data architecture

  • DataOps

Theme: ML in production

  • ML and continuous delivery / devops

  • Deploying ML on premises vs in the cloud

  • Cost management for ML in the cloud

  • Integrating ML models with other systems

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Research Talks:

Theme: Algorithms  

Theme: Applications  

Theme: Deep Learning  

Theme: Neuroscience and Cognitive Science  

Theme: Optimization    

Theme: Probabilistic Methods    

Theme: Reinforcement Learning and Planning  

Theme: Theory

 

Tips to a successful submission:

  • Be authentic. Our committee looks for original ideas in real-world scenarios with relevant examples.

  • Include as much detail about the presentation as possible.

  • Keep proposals free of marketing or sales pitches.

  • Make sure to describe clear value for attendees.

  • If you are not the speaker, provide the contact information of the person you’re suggesting.

  • Limit the scope: in 15-30 minutes, you won’t be able to cover ‘everything’. Pick a useful aspect, a particular technique etc.

  • If your talk is technical make sure to demonstrate practical teachings and takeaways

  • If your presentation is by, including the participation of a woman, person of colour, or underrepresented group please include that in the notes, as we strive include diversity in our lineup.

  • All submissions will go through a review process by our Steering Committee.