... I Studied 365 Data Visualizations in 2020. #machinelearning Abstract: The ecosystem for deploying SaaS applications includes countless tools for delivering an app to production, monitoring its performance, and deploying in real-time. We anticipate that FTL will enable the machine learning community to benefit from large datasets with uncertain labels in fields such as biology and medicine. The World of Learning Conference has cemented itself as a must-attend event for L&D professionals looking for practical solutions to common challenges. A set of co-operating systems need to be built that can serve the needs of the users. Use code KDNUGGETS for 25% off. Rebecca Knowles, Research Associate at National Research Council of Canada. Buy Tickets for this Toronto Event organized by 1.21GWS. Dillon Erb, CEO and Cofounder at Paperspace. ... 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 For data practitioners, you'll hear how to cut through the noise and find innovative solutions to technical challenges, learning from workshops, case studies, and P2P interactions. 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 are key prerequisites to focus yield high ROI on AI projects. Laptop or personal computer, strong, reliable wifi connection. Despite the remarkable results, these models are data-hungry and their performance relies heavily on the quality and size of the training data. Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering and Statistical Science at Duke University. Attendees will learn about the Bank’s customer segmentation approach, highlighting the flexibility of the model's given data availability. #analytics This talk will delve into Banorte's transformation journey into an AI-enhanced organization with data science projects yielding a net revenue that exceeds 3 billion USD during the past five years and avoiding transformational fatigue. Jose Murillo, Chief Analytics Officer and Francisco Martha Gonzalez, Payments, Digital Banking and IT Managing Director at Banorte. These event series bring together the latest technological advancements as well as practical examples to apply AI to solve challenges in business and society. 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. 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.. Q: Who will attend? Tickets are refundable up to 30 days before the event. WORLD MACHINE LEARNING SUMMIT. What You Will Learn: Theoretical foundation and interpretation of some of the commonly used heuristics in reinforcement learning such as entropy regularization and Gibbs/Boltzmann/Gaussian exploration. You can inquire at faraz@torontomachinelearning.com. 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. Online. Q: Which sessions are going to be recorded? The TAtech Digital Summit on AI & Machine Learning in Talent Acquisition January 19, 2021 – 11 AM ET – 8:00 AM PT – 3 PM GMT . This talk will show how to use A.I. Start Date: January 30th, 2020. Other examples with differences in data point label confidence include radiological or histopathological images or image segment labels, and measured resistance to cancer drugs. 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. Partner Event March 9, 2021 | 9:00 AM CST Virtual Event . Wednesday 9 December 2020. For Futher Information Visit The AI Summit Contact Us Page. 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. Mon, Jun 15, 9:00 AM EDT. Ari Kalfayan, Senior Business Development Manager - AI/ML & VC at Amazon Web Services. We will discuss what it means to build equity into data practices and what dismantling systemic racism can look like in technology (and the pitfalls to avoid). However, in aggregated data environments, confidence in the individual data points varies in a quantifiable manner by primary data source or measurement type. Specific techniques have been developed to help reduce bias at each stage of an ML system. Eventbrite, and certain approved third parties, use functional, analytical and tracking cookies (or similar technologies) to understand your event preferences and provide you with a customized experience. The Virtual Higher Education Summit 2020 (#HES2020) took place from 31 August – 2 September 2020. Causal assessments are usually done through A/B tests, which however are not always feasible. services are deployed to produce improvements to important business metrics, e.g. Abstract: There are high expectations about AI initiatives across different industries in North America. 15-16 Apr, RE.WORK AI in Retail & Marketing Summit. Christina Cai, Co-Founder & COO at Knowtions Research and Jennifer Nguyen, Lead Data Scientist at Sun Life. The goal of TMLS is to empower data practitioners, academics, engineers, and business leaders with direct contact to the people that matter most, and the practical information to help advance your projects. Go to Main Content. Event in Toronto, ON, Canada by Toronto Machine Learning Society on Thursday, November 2 2017 with 2.2K people interested and 166 people going. Toronto Machine Learning Summit and Expo 2020 (Virtual) Mon, Nov 16, 7:00 PM EST. 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. Conference Overview. Machine learning, deep learning, and AI are some of the fastest-growing and most exciting areas for knowledge workers - simultaneously, they are the key to untapped revenue sources and strategic insights for businesses. Dave S. Ali; Alice R. 28 attendees; MLOps, Production & Engineering World 2020. We will share results demonstrating generalizability towards existing emotion benchmarks from other domains. Lots of HR and recruiting conferences include a session or two on AI, but this TAtech Leadership Summit is different. Toronto Machine Learning Summit and Expo 2020 (Virtual) Mon, Nov 16, 7:00 PM EST. Deep Learning Summit, Toronto 2020 has 6 exhibitors including Alegion, Algorithmia, and Neurosoph. Each ticket includes:- Access 80+ hours of live-streamed content (incl. Artificial Intelligence and Machine Learning have become one of the hottest topics in business. In this talk, I will give a high-level overview of the key ideas that make this possible. Join Canada's Top AI And Machine Learning Strategies Summit 2020! It also discusses the main skills each stage requires, which can help companies in structuring their teams. Who would switch off Amazon recommendations entirely to do such an assessment? Last November, we had the opportunity to attend the Toronto Machine Learning Summit (TMLS) one of the most respected Machine Learning Conference & Exhibitions. Yes, the Virtual Conference is accessible via a smartphone or tablet. Ashish Bansal, Director, Recommendations Systems at Twitch. customer engagement, number of transactions, total profits. Biases may arise at different stages in machine learning systems, from existing societal biases in the data to biases introduced by the data collection or modeling processes. Toronto Machine Learning Summit (TMLS) — 2018. 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. Abstract: In recent years, fuelled by the advances in supervised machine learning, we have seen astonishing leaps in the application of deep neural networks. INTELLIGENT ROBOTIC PROCESS AUTOMATION SUMMIT. 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. 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. Abstract: This talk covers how AI will shape the future of media experience and how Yle is shaping its operations around this change. Mon, Jun 15, 9:00 AM EDT. Abstract: Large telecom providers (and many other industries) spend tens of millions of dollars each year reacting to customer issues. Event in Toronto, ON, Canada by Toronto Machine Learning Society on Thursday, November 2 2017 with 2.2K people interested and 166 people going. Needs a location. Abstract: This talk is designed to help you land your first 50 enterprise machine learning customers. Currently, this application is within the Bank’s international banking (IB) footprint, however, solutions are reuseable and scalable for application within the Canadian marketplace. And finally, how do you communicate the ROI of the project once it’s been deployed? In this talk, we will present our work at Google AI Research towards building GoEmotion, a large-scale dataset containing 58K social media comments labeled with a fine-grained emotion taxonomy, which is adaptable to multiple downstream tasks. Yes, you can submit an abstract here. Landing your first customer (0-1 customer), 2. This talk will introduce our work on Neural Projection computing, an efficient AI paradigm, and a family of efficient Projection Neural Network architectures that yield fast (e.g., quadratic speedup for transformer networks) and tiny models that shrink memory requirements by up to 10000x while achieving near state-of-the-art performance powering vision and NLP applications on billions of mobile devices. 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. 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. Check back for updates on the next Toronto Tech Summit! 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. 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. Given that the world and its data are ever more varied and dynamic, to take advantage of this power models need to be highly adaptable to represent the local diversity of events, people, markets, and operations. The Machine Learning service’s enhancements are handled by the Azure CICD pipeline. The related research is still in its infancy, and this talk reports some of the latest developments and suggests several directions for investigation. The Old Mill, Toronto, ON ... Suite 401 Toronto, Ontario M5V 3A8 Ai & Machine Learning Strategies Summit 2020. This presentation will be broken up into three parts: 1. Events are social. Event cost: From C$1,395. Toronto Machine Learning Summit and Expo 2020 (Virtual) Online event. Seminar series content will be practical, non-sponsored, and tailored to our ML ecosystem. 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. It starts by analyzing the difference between ML in research vs. in production, ML systems vs. traditional software, as well as myths about ML production. 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. How do you convince your stakeholders to put your ML models into production? We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. MLOps, Production & Engineering World 2020. 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. Today, AI researchers & practitioners increasingly use deep neural networks for many applications across different modalities and areas such as NLP, Vision, Speech, Conversational, and Multimodal AI. What You Will Learn: Practical advice and mistakes from having launched two top tier ML tools companies, Joe Greenwood, Vice President Data Strategy - North America at Mastercard. Deep Learning Summit. Source: Re-Work. Shirin Akbarinasaji, Senior Data Scientist; Navid Kaihanirad, Data Scientist; Cheng Chen, Data Scientist at Scotiabank. Although it is a fundamental step for many data science tasks, an efficient and standard framework is absent. Find out more about how your privacy is protected. When will the recordings be available and do I have access to them? 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. Includes unique discount codes and submission deadlines. The E2E machine learning solution was implemented as a web service using MLflow, Azure Kubernetes Services. Thu, Nov 2, 2017, 9:00 AM: Hello Folks!Based on the needs of our community we've created a 2 day event for you, bringing together 1. practitioners 2. enthusiasts and 3. businessesThe content will be p Machine Learning in NLP & Computer Vision Summit, Irish Mass Spectrometry Society Annual Conference, MLOps World; Machine Learning in Production 2021, Fordham Finance Society: Trending in Finance 6th Annual Conference, South Carolina Thoracic Society - 2021 Annual Conference, Introduction to Machine Learning [Live-Online]. Q: Can I watch the live stream sessions on my phone or tablet computer? Where to focus AI initiatives to have a large organizational impact: revenue or cost? Start Date: January 30th, 2020. Speakers this year include Mastercard, Google, Facebook, Uber, LG, Haliburton, Telus, Sunlife, Uber, KFC, and more!. At each RE•WORK event, we combine the latest technological innovation with real-world applications and practical case studies. Matt Sheehan, Fellow at The Paulson Institute. Online Events Jacopo Tagliabue, Lead A.I. What You Will Learn: Exciting directions and opportunities for assisting machine learning with quantum computers. 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. 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). 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. Learn how they built a machine learning system for automatically moderating comments from millions of readers. This list provides an overview with upcoming ML conferences and should help you decide which one to attend, sponsor or submit talks to. However, numerous challenges to the acquisition, storage, and utilization of data as well as the development of practical machine learning algorithms and change management principles need to be considered. This talk will provide an overview of the process of applying ML into healthcare and the legal and ethical considerations needed for data access and application. Virtual Toronto Tech Summit 2020 . How emotions can be detected from textual content for business use cases & research purposes, 2. 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. What You Will Learn: Neural machine translation, applications of machine learning to Indigenous languages, challenges of domain adaptation in low-resource settings, Jaakko Lempinen, Head Of Customer Experience at Yle. This phenomenon—known as the cold start problem—is a pain point for almost any AI company that wants to scale. 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. recordings)- Talks for beginners/intermediate & advanced- Network and connect through our event app- Q+A with speakers- Channels to share your work with the community- Run your chat groups and virtual gatherings!- Hands-on Workshops*PLEASE NOTE BONUS WORKSHOPS ARE ON THE 16TH AND 17TH OF NOVEMBER.
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