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Online. Source: Re-Work. Explore how deep learning will impact healthcare, manufacturing, search & transportation. Here are the top 22 machine learning conferences in 2020: 1. 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.. 5-6 Apr, Middle East Banking AI & Analytics Summit. Mai Phan, Data Expert Equity, Inclusion and Human Rights at Toronto Police Service. Winston Li, Founder at Arima and Doug Creighton, Data Science Lead at Statflo Inc. Abstract: A synthetic dataset is a data object that is generated programmatically, and it is often necessary for situations where data privacy is a concern, or when collecting data is difficult or costly. Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering and Statistical Science at Duke University. #deep_learning We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. What You Will Learn: How to set up your model monitoring from scratch, and how to prioritize different metrics, Rich Caruana, Principal Researcher at Microsoft Research. Alba Cervera-Lierta, Postdoctoral Researcher at the University of Toronto. Q: What are the technical requirements to be able to participate? Causal assessments are usually done through A/B tests, which however are not always feasible. Our, Director of Data Science, Ashwin Swarup, will be a part of this event as a Speaker. 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. Practitioners are leveraging and expanding their expertise to become high-impact global leaders. 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. 2) How new methods in intelligible machine learning can help mitigate this risk. Deep Learning Summit, Toronto 2020 has 6 exhibitors including Alegion, Algorithmia, and Neurosoph. We will discuss challenges, applications of state of the art models, and future use cases. Learn how they built a machine learning system for automatically moderating comments from millions of readers. We will unpack the idea of race as relationships and race as data in its historical and current contexts. To adapt to the current environment and the growing demand for delegates to enjoy the conference experience in an online manner, The AI Summit 2021 will come to you as a virtual event.. Tim is a long-time attendee, contributor and advocate of the Embedded Vision Summit, remembering the event in its early days, long before the move to long trousers. We'd like to welcome you to join us in celebrating the top achievements in AI/ML from the perspective of research and applications and business strategy, across all industries. Start Date: January 30th, 2020. 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. 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. 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. Abstract: This talk covers what it means to operationalize ML models. What You Will Learn: In this talk, we will share lessons we learned in answering three questions and the metrics stakeholders care about. 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). Abstract: 'Race' is a concept, a tool, and a structure that defines a set of relationships between people. Shreyansh Daftry, AI Research Scientist at NASA Jet Propulsion Laboratory. 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. Abstract: There are high expectations about AI initiatives across different industries in North America. 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. The scale of users, size of the catalog, speed of reaction to user actions are some of the factors that make such systems very challenging to build. 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. Last November, we had the opportunity to attend the Toronto Machine Learning Summit (TMLS) one of the most respected Machine Learning Conference & Exhibitions. 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. Landing your first customer (0-1 customer), 2. This often limits the accuracy of models that can safely be deployed in mission-critical applications such as healthcare where being able to understand, validate, edit, and ultimately trust a model is important. Log in or sign up for Eventbrite to save events you're interested in. Wednesday 9 December 2020. Abstract: The quality of online comments is critical to the Washington Post. The international event addressed the question “How can we assure quality and transformative learning for sustainable development?” and was co-organised by the COPERNICUS Alliance , saguf , td-net , the University of Bern , and the University of Lausanne ( ⭢ Organizers & Supporters ) Q: Can I speak at the event? Abstract: Tubi is an advertiser based video-on-demand service that allows its users to watch content online. Come and expand your network with machine learning experts and further your own personal & professional development in this exciting and rewarding field. Brandy Freitas, Senior Data Scientist at Precisely. Abstract: One of the fundamental goals in the emerging field of quantum machine learning is to build trainable quantum computing algorithms. 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. AI & Machine Learning Strategies Summit enables senior executives to access cutting edge strategic and technological content, in an environment that is conducive to forging lasting business relationships. Q: How can I contact the organizer with any questions? It is a 2 day event organised by Strategy Institute Inc and will conclude on 16-Sep-2020. 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. 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. In this talk, we provide concrete examples of intractable ML tasks that could be enhanced with near-term devices. The related research is still in its infancy, and this talk reports some of the latest developments and suggests several directions for investigation. Sedef Akinli Kocak, Project Manager at Applied AI Project, Vector Institute. What You Will Learn: How to maximize the value of geospatial data using machine learning and artificial intelligence techniques, business problems that can be tackled in a variety of industries using this type of data, and how to utilize algorithms specific to spatial data. Despite the remarkable results, these models are data-hungry and their performance relies heavily on the quality and size of the training data. Q: Who will attend? ( See abstract at the bottom). What You Will Learn: The current state of quantum computation. The Machine Learning service’s enhancements are handled by the Azure CICD pipeline. 15-16 Apr, RE.WORK AI in Retail & Marketing Summit. Dillon has great clarity on macro trends within the infrastructure space while maintaining pragmatism about incorporating the latest open-source tools. 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. Furthermore, transitioning to a career in practicing AL/ML, or managing ML and AI-driven businesses, are less than straightforward. 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. *Content is non-commercial and speaking spots cannot be purchased. 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. 1) The risk of using machine learning in healthcare when you can't understand what the model is learned. 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. 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. Ali Madani, Leader of Machine Learning at Cyclica Incorporation. It also discusses the main skills each stage requires, which can help companies in structuring their teams. How to measure AI contribution to the bottom line, 2. DATE:July 24,2020. We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. Meet hundreds of senior Artificial Intelligence and Machine Learning leaders at … 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. In this talk, I will provide an overview of the NLP project and share how industry participants gained practical knowledge through pre-training large scale language models, learned theoretical concepts from leading NLP practitioners, and broadened their professional network through collaborations with participating sponsors. 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. These hurdles limit the accessibility many organizations have to NLP capabilities, putting the significant benefits advanced NLP can provide out of reach. Lastly, we will share how organizations could use this dataset to train custom models for their use cases. Abstract: Building recommendation systems in production that can serve millions of customers goes way beyond just having a great algorithm. Abstract: Large telecom providers (and many other industries) spend tens of millions of dollars each year reacting to customer issues. BACKGROUND. Please register via https://bit.ly/TMLS2020Hopin, We'd like to welcome you to join us in celebrating the top achievements in AI/ML from the perspective of research and applications and business strategy, across all industries. Differences in label confidence make model building challenging, as the optimization cannot be done while amalgamating all the data points in the training process. 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. 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. Partner Event March 9, 2021 | 9:00 AM CST Virtual Event . Toronto Machine Learning Summit and Expo 2020 (Virtual) Mon, Nov 16, 7:00 PM EST. #data_science This will also present comparisons between CheckList and the status quo in a case study at Microsoft and a user study with researchers and engineers in which it will show that CheckList is a really helpful process and tool for testing and finding bugs in NLP models, both for practitioners and researchers. For more information please review our cookie policy. This talk distills learnings from building recommendation systems servings millions of customers across multiple companies like Twitter, Twitch, Capital One into a set of commonly used design patterns that you can use right away. Whether you are developing your first machine learning application, creating an enterprise ML infrastructure startup, or creating new Machine/Deep Learning tools, this hands-on session is designed to share practical strategies, growth hacks, and specific techniques to use that will win you your first customers and scale. 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. These biases may impact the performance of various components of ML systems, from offline training to evaluation and online serving in production systems. Each ticket includes:- Access 80+ hours of live-streamed content (incl. 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. 1. Everyone is welcome. What You Will Learn: This is about applying cutting edge machine learning domain in the banking domain. 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". Contact Us Now! Finally, I will explain the state of development of experimental quantum computers and future prospects. For Futher Information Visit The AI Summit Contact Us Page. The approach behind pricing analytics can be formulated as customer segmentation and constrained optimization problems in order to increase sales and/or revenue. However, it’s not very common to come across companies that have both. #data_analytics_training. #data_science_course Ari Kalfayan, Senior Business Development Manager - AI/ML & VC at Amazon Web Services. Abstract: Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. The TAtech Digital Summit on AI & Machine Learning in Talent Acquisition January 19, 2021 – 11 AM ET – 8:00 AM PT – 3 PM GMT . Business Executives, Ph.D. We demonstrate that using FTL to learn stepwise, across the label confidence distribution, results in higher performance compared to deep neural network models trained on a single confidence range. Artificial Intelligence and Machine Learning Summit 2020.

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