Source: Re-Work. During this talk, we’ll discuss the emerging patterns, state-of-the-art methods, and best practices leading companies are using to productionize ML/DL models. Log in or sign up for Eventbrite to save events you're interested in. Events are social. Toronto Machine Learning Summit Visit the Innodata virtual event booth November 19th for the presentation “Bogged Down by Annotation, Why SMEs Should Do the Heavy Lifting” with Innodata’s Chief Product & Marketing Officer. by Toronto Machine Learning Society (TMLS). The event will have three tracks: One for Business, one for Advanced Practitioners/Researchers, and one for applied use-cases (Focusing on various Industries). Canada's Top AI and Machine Learning Summit Abstract: Deep learning has changed the computing paradigm. Paco Nathan, Computer Scientist at Derwen Inc. Abstract: We recently conducted an industry survey of firms that have natural language systems in production. Presenters will speak to optimization realized through the approach and provide insights into how the business was considered throughout the data and analytics journey. 06 , March , 2020 - Toronto. Abstract: There are high expectations about AI initiatives across different industries in North America. Q: Can I get a training certificate? This talk will describe sources of bias in ML technology, why addressing bias matters, and techniques to mitigate bias, with examples from the speaker's work on inclusive AI at Pinterest. What You Will Learn: How AI/ML is being used by NASA to enable the next frontier in robotics space exploration; Challenges in deploying AI/ML for safety-critical systems, Nadia Fawaz, Applied Research Scientist at Pinterest. This talk will outline the business imperative for robust and ethical model design and Mastercard's approach to leveraging a global data-strategy that sets the highest standards for the responsible use of data and AI though human-centered data-design while ensuring local compatibility and functionality through a regional approach to data sourcing and quality, model testing and governance, and internal data literacy. AI & Machine Learning Summit 2020 will take place at the Hyatt Regency Boston in Boston, MA between May 19 - 20, 2020 and is a two-day immersion into the leading AI and machine learning use cases, strategies and technologies that every organization should know about. Why should I attend the Toronto Machine Learning Society (TMLS) 2020 Annual Conference & Expo: Developments in the field are happening fast: For practitioners, it's important to stay on top of the latest advances; for business leaders, the implementation of new technology brings specific challenges. The project involved 60 participants: 23 Vector researchers and staff with expertise in machine learning and NLP along with 37 industry technical professionals from 16 Vector sponsor companies. Methodology: Scotiabank proposes to use model-based recursive partitioning (MOB) which uses product characteristics and customer attributes as input and customer willingness to pay as output to segment customers. We propose a deep neural network approach called Filtered Transfer Learning (FTL) that defines multiple tiers of data confidence as separate tasks in a transfer learning setting. The ultimate list of the top Machine Learning & Deep Learning conferences to attend in 2021. What You Will Learn: Real-world learnings from putting deep learning models rapidly from research to production through solid Ops and orchestration. This talk provides a brief overview of Indigenous language technology projects at the National Research Council of Canada, before focusing on one project in particular: the development of neural machine translation systems to translate between Inuktitut and English. Details about data for training own models, Emeli Dral, CTO and Co-founder at Evidently AI. In this presentation, we study a specific synthetic data generation task called downscaling, a procedure to infer high-resolution information (e.g., individual-level records) from low-resolution variables (e.g., an average of many individual records), and propose a multi-stage framework. By contrast, while we’ve seen explosive growth in the adoption of the machine and deep learning (ML/DL) across industries, putting ML/DL models into production isn’t as well supported. This makes it easy to understand what a model has learned and to edit the model when it learns inappropriate things, making it possible for medical experts to understand and repair a model as most clinical data have unexpected problems that is quite critical. Abstract: AI-driven, including ML models, provide the capability to process a greater volume and variety of data to power new global platforms and products and to optimize global business operations. The capacity to implement and demonstrate high ROI AI projects changes this dynamic. Introduction of Toronto Machine Learning Summit. The Big Data & Analytics Summit Canada is designed to provide data executives with current trends, strategic insights, and best practices trending in technology, data, AI, machine learning, risk management, and retaining talent.. What You Will Learn: Attribution models for site search engines are stuck at "last-action" and Google Analytics-style reporting: since A/B testing the search bar is impossible, it is really hard to make informed business decisions involving the search experience. In this talk, we demonstrate how this problem can be addressed by aggregating data across sources and leveraging previously trained models. Scientist at Coveo. The event, which brings together university presidents, world-class researchers, political leaders and senior executives from industry in one of the most prestigious gatherings of its kind in the world, will take place from 1 to 3 September 2020. What You Will Learn: You'll learn about China's role in the global flows of AI research talent, and what implications this has for government policy in the US, Canada, and Europe. Abstract: Recent advances in machine translation has resulted in systems of very high quality, but only for a very limited set of the world’s more than 7000 languages. Abstract: Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. TIME: 14:00 IST / 09:30BST / 18:30 AEST / 16:30 ACT(3HOURS) REGISTER HERE. Lastly, we will share how organizations could use this dataset to train custom models for their use cases. The speaker will give few examples of how ideas are scaled into products across the whole organization and will also talk about how the culture changes within organizations as they start to benefit more from progressive data solutions – what are the future skills that every organization should have and how to get started with the change. What You Will Learn: How to deal with data points with different levels of confidence in a deep learning setting, Gaurav Nemade, Product Manager at Google AI and Dana Movshovitz-Attias, Software Engineer at Google Research. The failure modes of machine learning systems are also different from those of traditional software applications. Finally, I will explain the state of development of experimental quantum computers and future prospects. Abstract: Large telecom providers (and many other industries) spend tens of millions of dollars each year reacting to customer issues. There’s a record amount of exciting Machine Learning (ML) and Deep Learning conferences worldwide and keeping track of them may prove to be a challenge. Machine Learning Developers Summit 2020 (#MLDS2020) brings together the India’s leading Machine Learning innovators and practitioners to share their ideas and experience about machine learning tools. Yes, we will have talks that cover Finance, Healthcare, Retail, Transportation, and other key industries where applied ML has made an impact. Eventbrite - Toronto Machine Learning Society (TMLS) presents Toronto Machine Learning 'Micro-Summit' Series ( TMLS) - Finance Special Focus - Wednesday, 15 April 2020 - … Practitioners are leveraging and expanding their expertise to become high-impact global leaders. Conference Overview. Abstract: Working with and analyzing geospatial data requires a different and often nuanced approach from most data types, especially to derive spatial predictions and detect patterns using machine learning applications. 2020 edition of AI & Machine Learning Strategies Summit will be held at Old Mill Toronto, Toronto starting on 15th September. Machine Learning; Business. Lots of HR and recruiting conferences include a session or two on AI, but this TAtech Leadership Summit is different. What You Will Learn: How to build a system that utilizes both human and machine learning moderation to efficiently scale to millions of reader comments. Last November, we had the opportunity to attend the Toronto Machine Learning Summit (TMLS) one of the most respected Machine Learning Conference & Exhibitions. Online Events If we use interpretable machine learning models, they come with their own explanations, which are faithful to what the model actually computes. Douglas Hofstadter called analogy-making “the core of cognition”, and Hofstadter and co-author Emmanuel Sander noted, “Without concepts, there can be no thought, and without analogies, there can be no concepts.” In this talk, I will reflect on the role played by analogy-making at all levels of intelligence, and on how analogy-making abilities will be central in developing AI systems with human-like intelligence. Run your chat groups and virtual gatherings! What You Will Learn: Practical considerations in building real-life recommendation systems, David Duvenaud, Assistant Professor at the University of Toronto, What You Will Learn: You'll learn about the main existing approaches for building flexible time series models, and their strengths and weaknesses, Nathan Killoran, Head of Software & Algorithms at Xanadu Quantum Technologies. Learn how they built a machine learning system for automatically moderating comments from millions of readers. The Virtual Higher Education Summit 2020 (#HES2020) took place from 31 August – 2 September 2020. The Old Mill, Toronto, ON ... Suite 401 Toronto, Ontario M5V 3A8 Ai & Machine Learning Strategies Summit 2020. Accounting; Business Administration; Human Resources Management; People Analytics; Risk Management; Chartered Business Valuator Program; Marketing, Communications & Design. Event in Toronto, ON, Canada by Toronto Machine Learning Society on Thursday, November 2 2017 with 2.2K people interested and 166 people going. Much like the similarly named International Conference on Machine Learning, the International Conference on Machine Learning and Applications, ICMLA 2020, is designed to bring together academic and industry researchers. Many data scientists and analysts are not used to fully leveraging the power of geospatial data, and often don't know what business questions to ask, aren't aware of which algorithms are available to them to enrich their models, or resort to eliminating spatial variables entirely in order to use the data with common machine learning algorithms. #data_science_training In addition, the Harvard Business School has written and taught a case study on Jose’s analytics and digital transformation leadership. The event, which brings together university presidents, world-class researchers, political leaders and senior executives from industry in one of the most prestigious gatherings of its kind in the world, will take place from 1 to 3 September 2020. Despite significant effort, there has been a disconnect between most quantum ML proposals, the needs of ML practitioners, and the capabilities of near-term quantum devices towards a conclusive demonstration of meaningful quantum advantage in the near future. Toronto Machine Learning Summit Visit the Innodata virtual event booth November 19th for the presentation “Bogged Down by Annotation, Why SMEs Should Do the Heavy Lifting” with Innodata’s Chief Product & Marketing Officer. Artificial Intelligence and Machine Learning have become one of the hottest topics in business. Speakers this year include Mastercard, Google, Facebook, Uber, LG, Haliburton, Telus, Sunlife, Uber, KFC, and more!. Alegion Alegion’s platform blends human and machine intelligence to provide accurate labeled data used to train or validate machine learning models. Shirin Akbarinasaji, Senior Data Scientist; Navid Kaihanirad, Data Scientist; Cheng Chen, Data Scientist at Scotiabank. Abstract: The data scientist’s job does not finish when the model is shipped.