Utilizing machine learning and the power of robotic process automation (RPA), we have set out to determine a way to predict which customers are going to reach out with an issue before they actually do – empowering us to take immediate action, to correct the issue, before a customer notices and before they have to spend their valuable time contacting us. #data_analytics 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. Your email will only be seen by the event organizer. #machinelearning Laptop or personal computer, strong, reliable wifi connection. Furthermore, there is a large amount of metadata in the form of actors, ratings, year of release, studio, etc. Scientist at Coveo. Abstract: There are high expectations about AI initiatives across different industries in North America. If you’re looking to regain momentum and fast-track growth with smarter data, you won’t want to miss Accelerate 2021: Data Analytics Summit, presented by Wavicle DataSolutions, a Databricks Partner. Abstract: Tubi is an advertiser based video-on-demand service that allows its users to watch content online. We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. Q: What's the refund policy? Developing and employing NLP models in the industry has become progressively more challenging as model complexity increases, data sets grow in size, and computational requirements rise. CSC 311 Fall 2020: Introduction to Machine Learning Overview. The challenge of mixed confidence training data is not restricted to the domain of protein and drug interaction; in practice, data labeling is done based on either computational algorithms or human experts (or even non-experts), and neither approach is perfect. Validating your business model (1-10 customers). Location: San Francisco, California. Results: This pricing product has been used in three different countries: Peru, Columbia, and Mexico in various products such as a mortgage, SPL, and term deposit with great feedback that has helped Scotiabank to capture international banking customer behavior and their price sensitivity more promptly. The talk is designed so that those managing projects (e.g., data science directors/managers) and those executing the work (e.g., data scientists/analysts) can walk away with tips to help their ML projects start and close off successfully. ... Reinforcement Learning Summit Toronto, Canada: Oct 19 - Oct 20, 2021: NA: Discount: AI for Good Summit Toronto, Canada: Nov 11 - Nov 12, 2021: NA: Discount: ODSC West 2021 Tue, Sep 15 – 16, 2020. We argue that to reach this target, the focus should be on areas where ML researchers are struggling, such as generative models in unsupervised and semi-supervised learning, instead of the popular and more tractable supervised learning tasks. Virtual Toronto Tech Summit 2020 . What You Will Learn: In this talk, the speaker will present a novel method for generating synthetic datasets (which has not yet been published) as well as 2 real-world case studies of Arima's partners on how synthetic data has improved their model performances. Accounting; Business Administration; Human Resources Management; People Analytics; Risk Management; Chartered Business Valuator Program; Marketing, Communications & Design. As such, more creative thinking is needed to convince stakeholders that your ML solutions can be trusted and bring value. Q: Are there ID or minimum age requirements to enter the event? Includes unique discount codes and submission deadlines. Location: San Francisco, California. Differences in label confidence make model building challenging, as the optimization cannot be done while amalgamating all the data points in the training process. 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. Attendees of the event received full access to all talks and presentations and the opportunity to engage in Q&A sessions after each talk. 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. Online. Abstract: This talk will discuss CheckList, a task-agnostic methodology, and tool for testing NLP models inspired by principles of behavioral testing in software engineering, showing a lot of fun bugs that were discovered with CheckList, both in commercial models (Microsoft, Amazon, Google) and research models (BERT, RoBERTA for sentiment analysis, QQP, SQuAD). In particular, it will show how deep learning models can be used to assess how much revenue in a digital shop comes from interactions with search and recommendation APIs. Explanations for black-box models are not reliable and can be misleading. Join the AI and Machine Learning Strategies Summit to learn about the latest technologies and imple... 3 °C | Thursday, February 4, 2021 toronto.com Details about data for training own models, Emeli Dral, CTO and Co-founder at Evidently AI. We will share the technical challenges with building the comment moderation platform and how we raised the quality of online conversations with machine learning. And if they do, each team often works in a vacuum, siloed from each other. Business Executives, Ph.D. What are key prerequisites to focus yield high ROI on AI projects. This generally takes the form of large call center and repair technician workforces that are waiting for an issue to happen, in order to help solve it. However, in aggregated data environments, confidence in the individual data points varies in a quantifiable manner by primary data source or measurement type. ML has become increasingly central both in AI as an academic field, and in industry. Abstract: How do you get buy-in from leadership to sponsor your ML project? When evaluating the contribution of a new service, it is crucial to be able to answer the attribution question: how much of my target outcome would have been achieved even in the absence of the A.I. Melanie Mitchell, Professor at the Portland State University. More information about Deep Learning Summit Toronto 2020. If we use interpretable machine learning models, they come with their own explanations, which are faithful to what the model actually computes. It starts with the gap between ML in research and ML in production. Mon, Jun 15, 9:00 AM EDT. This presentation will be broken up into three parts: 1. Abstract: This talk covers how AI will shape the future of media experience and how Yle is shaping its operations around this change. #data_engineering Deep Learning Summit. Toronto Machine Learning Summit and Expo 2020 (Virtual) Online event. 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. 10:10 – 10:45 Opening Keynote: What You Will Learn: The challenges, the solutions, the effectiveness, and the remaining issues, including technology progress and institutional reform. Machine learning (ML) is a set of techniques that allow computers to learn from data and experience, rather than requiring humans to specify the desired behaviour by hand. What You Will Learn: This talk outlines the challenges and approaches to designing, developing, and deploying ML systems. We will unpack the idea of race as relationships and race as data in its historical and current contexts. Start Date: January 30th, 2020. by Toronto Machine Learning Society (TMLS). Big Data and AI Toronto is going virtual for its 5th edition! The Toronto Machine Learning Summit (TMLS) ... (2020) as an example of a firm that has developed high ROI artificial intelligence applications. In addition, the Harvard Business School has written and taught a case study on Jose’s analytics and digital transformation leadership. Speakers this year include Mastercard, Google, Facebook, Uber, LG, Haliburton, Telus, Sunlife, Uber, KFC, and more!. While these are questions universal to any industry, they are particularly challenging to answer in the insurance industry because of its highly regulated and risk-averse nature. 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. Here are the top 22 machine learning conferences in 2020: 1. 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. What You Will Learn: ML infrastructure and tool stacks are endlessly interesting and convoluted. Abstract: This talk tackles the process of building scalable deep learning pipelines for hundreds of model training on giant time-series datasets and on how it helped saved 80% of the cost along the way. Learn how they built a machine learning system for automatically moderating comments from millions of readers. What You Will Learn: In this talk, you will see real examples of the cold start problem and how it can prevent businesses from effectively and efficiently growing. Models developed only with a global perspective can result in missing valuable insights, and potential harms from models that are biased in their results, or inadvertently exclude groups in society. Machine Learning Developers Summit 2021 (MLDS20) is the gold standard for India’s data science & Machine learning ecosystem for gaining exposure to ML tools and frameworks, evaluating new projects, hardware & software challenges of building complex ML systems, the right tools and platforms, languages, software and standards. Review the 2020 agenda for this year's program info. Tue, Sep 15 – 16, 2020. The conference is designed to shine a spotlight on international research in machine learning and deep learning with an emphasis on related applications, algorithms, and systems. Use code KDNUGGETS for 25% off. Dillon has great clarity on macro trends within the infrastructure space while maintaining pragmatism about incorporating the latest open-source tools. Shreyansh Daftry, AI Research Scientist at NASA Jet Propulsion Laboratory. Tue, Sep 15th & Wed, Sep 16th, 2020. What You Will Learn: You'll learn how modern AI and ML are approaching the problem of conceptual abstraction and analogy-making, and how these approaches compare with human abilities in these areas. Source: Re-Work. Abstract: While most existing reinforcement learning (RL) research is in the framework of Markov Decision Processes (MDPs), it is important and indeed necessary, both theoretically and practically, to consider RL in continuous time with continuous feature and action spaces, for which stochastic control theory offers a natural underpinning. Abstract: This talk is designed to help you land your first 50 enterprise machine learning customers. You may also find my experience helpful, which is that we have never needed a black box model for a high stakes decision because we have always been able to construct an interpretable model that is at the same level of predictive performance as the best black box we could find. Data and AI Summit is Europe's largest data & machine learning conference in the world. A set of co-operating systems need to be built that can serve the needs of the users. 2020 edition of AI & Machine Learning Strategies Summit will be held at Old Mill Toronto, Toronto starting on 15th September. Yes, there will be spaces for company displays. Toronto, Canada. 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. What You Will Learn: You will learn about and better understand what systemic racism is, the historical legacy of race data, and how to challenge and question data practices for a more equitable society. Online Science & Tech Conferences This talk will give examples of neural-symbolic AI implemented using the OpenCog AI framework, including semantics-preserving hypergraph embeddings and probabilistic logic-based explanations of ML-identified data patterns. Canada's Top AI and Machine Learning Summit All sessions will be recorded during the event (provided speaker permissions) and will be made available to attendees approximately 2-4 weeks after the event and be available for 12 months after release. Shirin Akbarinasaji, Senior Data Scientist; Navid Kaihanirad, Data Scientist; Cheng Chen, Data Scientist at Scotiabank. 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.. It is a 2 day event organised by Strategy Institute Inc and will conclude on 16-Sep-2020. 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. The talk ends with a survey of the ML production ecosystem, the economics of open source, and open-core businesses. Everyone is welcome. Yes, you can submit an abstract here. Come and expand your network with machine learning experts and further your own personal & professional development in this exciting and rewarding field. As well, to help data practitioners, researchers and students fast-track their learning process and develop rewarding careers in the field of ML and AI. Christina Cai, Co-Founder & COO at Knowtions Research and Jennifer Nguyen, Lead Data Scientist at Sun Life. The 2nd Annual Responsible Machine Learning Summit will take place on October 9, 2020 and will be a fully virtual event. Presenters will speak to optimization realized through the approach and provide insights into how the business was considered throughout the data and analytics journey. ), - How we aim to operationalize model findings quickly in an environment with legacy systems. In order to enable AI experiences in real-time across all users and devices, ML models have to run efficiently on the Cloud and personal devices on the Edge (e.g., mobile phones, wearables, IoT) which have limited computing capabilities. - How and why the machine learning models break; - How to analyze production model performance, data drift and monitor data quality; - How to set up your monitoring strategy in a pragmatic way. The benefits of scaling global models through regional data strategies will be illustrated with examples from fraud detection, credit decisioning, economic modeling, and understanding consumer preferences. This allows us to train quantum computers in largely the same way as we do neural networks, even using familiar software tools like TensorFlow and PyTorch. Mitigating bias in machine learning systems is crucial to successfully achieve the company's mission to "bring everyone the inspiration to create a life they love". Scaling your business (10-50 customers) This presentation is designed to leave you with practical tips to help you acquire new customers, no matter your funding stage. Furthermore, transitioning to a career in practicing AL/ML, or managing ML and AI-driven businesses, are less than straightforward. I will share some of the technical challenges that we encountered throughout the project and how we overcome them. Rebecca Knowles, Research Associate at National Research Council of Canada. Der ML Summit ist das große Trainingsevent für alle Entwickler:innen, IT-Projektleiter:innen und Product Owner. Dubai, UAE. I will present what are the state-of-the-art quantum algorithms, its advantages, and limitations. Online. What You Will Learn: Cutting-edge technology & practical applications for efficient Deep Learning on the Edge & Cloud, Mary Jane Dykeman, Partner and Co-Founder at INQ Data Law and Muhammad Mamdani, Vice President, Data Science and Advanced Analytics at Unity Health Toronto. Lots of HR and recruiting conferences include a session or two on AI, but this TAtech Leadership Summit is different. #machine_learning See who else is going to Toronto Machine Learning Summit 2020, and keep up-to-date with conversations about the event. What You Will Learn: The 2020 industry landscape for NLP use cases in production; the relative "market share" for the popular open-source libraries/frameworks; and analysis of cloud service usage and failure cases; plus industry drivers for accuracy vs. cost in new NLP advances, Azin Asgarian, Applied Research Scientist at Georgian and Franziska Kirschner, Research Lead at Tractable. Watch Queue Queue It then goes over the principles of good ML systems design and introduces an iterative framework for ML systems design, from scoping the project, data management, model development, deployment, maintenance, to business analysis. Start Date: January 30th, 2020. Abstract: 'Race' is a concept, a tool, and a structure that defines a set of relationships between people. In this work, we apply a transfer learning approach to improve predictive power in noisy data systems with large variable confidence datasets. Alegion Alegion’s platform blends human and machine intelligence to provide accurate labeled data used to train or validate machine learning models. What You Will Learn: How to test NLP models, Patrick Cullen, Director of Data Science and Ling Jiang, Senior Data Scientist at The Washington Post. See Attendee Demographics and a list of the Attendee Titles from our past event here. Deep Learning Summit, Toronto 2020 has 6 exhibitors including Alegion, Algorithmia, and Neurosoph. 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. 5-6 Apr, Middle East Banking AI & Analytics Summit. Introduction of Toronto Machine Learning Summit. Events are social. What You Will Learn: The current state of quantum computation. TMLS is not a sales pitch - it's a connection to a deep community that is committed to advancing ML/AI and to create and deliver value and exciting careers for Businesses and Individuals. What You Will Learn: Attendees will gain an understanding of the principles of knowledge translation in applied machine learning in healthcare and understand issues related to privacy and ethics as well as legal considerations. Abstract: Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. Check back for updates on the next Toronto Tech Summit! Description: Learn how to use AI to solve common business problems. The Machine Learning service’s enhancements are handled by the Azure CICD pipeline. Times Higher Education’s World Academic Summit 2020 will be held in partnership with the University of Toronto next September.. Contact Us Now! 3) Agnostic pipeline that can be reusable for other pricing use cases. Paco Nathan, Computer Scientist at Derwen Inc. Abstract: We recently conducted an industry survey of firms that have natural language systems in production. We also live in the age of UX where user-centricity is no longer the exception or a market differentiator - it is now the norm. Dillon Erb, CEO and Cofounder at Paperspace. The World of Learning Conference has cemented itself as a must-attend event for L&D professionals looking for practical solutions to common challenges. Data Summit Connect 2020 is a new free webinar series taking place June 9 - 11, 2020 and will focus on analytics, machine learning, AI, data lakes, and much more. Q: Can I get a training certificate? Abstract: The talk will give an overview of China's AI/ML ecosystem, and a deep dive into its capabilities when it comes to leading-edge research in neural networks. Despite the vast opportunities that lie within our data, there are also explicit challenges to revealing their potential. Q: How can I contact the organizer with any questions? However, much of the Deep Learning revolution has been limited to the Cloud and highly specialized hardware. In addition, attendees were eligible to win giveaways during the event. 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. Use code KDNUGGETS for 25% off. The TMLS initiative is dedicated to helping promote the development of AI/ML effectively, and responsibly across all Industries. This one-day conference convened 75 cultural heritage professionals (roughly 50 from outside the Library of Congress and 25 staff from within) to discuss the on-the-ground applications of machine learning technologies in libraries, museums, and universities.