Abstract: In this talk, I will overview the basic concepts of quantum computing and its applications. 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. See who else is going to Toronto Machine Learning Summit 2020, and keep up-to-date with conversations about the event. Specifically, this talk will discuss the following: 1) How synthetic data is generated from aggregated sources like census, 2) Why is this important from an application perspective, and. Deep Learning Summit. #deep_learning 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. The findings can be generalized to many other settings, to assess and monitor the performance of existing ML pipelines even in the absence of A/B testing. Keep up with Toronto Machine Learning Summit 2020. Lastly, we will share how organizations could use this dataset to train custom models for their use cases. The results are pervasive across technology subcategories within the field of natural language: parsing, natural language understanding, sentiment detection, entity linking, speech recognition, abstractive summarization, and so on. Q: Will you focus on any industries in particular? Lots of HR and recruiting conferences include a session or two on AI, but this TAtech Leadership Summit is different. 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. Join Canada's Top AI And Machine Learning Strategies Summit 2020! Artificial Intelligence and Machine Learning have become one of the hottest topics in business. 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. Introduction of Toronto Machine Learning Summit. - 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. Last November, we had the opportunity to attend the Toronto Machine Learning Summit (TMLS) one of the most respected Machine Learning Conference & Exhibitions. Join the AI and Machine Learning Strategies Summit to learn about the latest technologies and imple... 3 °C | Thursday, February 4, 2021 toronto.com Mon, Jun 15, 9:00 AM EDT. Online Science & Tech Conferences Dave S. Ali; Alice R. 28 attendees; MLOps, Production & Engineering World 2020. ML has become increasingly central both in AI as an academic field, and in industry. See who else is going to Toronto Machine Learning Summit 2020, and keep up-to-date with conversations about the event. Explore how deep learning will impact healthcare, manufacturing, search & transportation. Who would switch off Amazon recommendations entirely to do such an assessment? 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. Our survey results explore both the contours of the evolving landscape as well as the industry adoption and business trends for NLP. Contact Us Now! 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. Ari Kalfayan, Senior Business Development Manager - AI/ML & VC at Amazon Web Services. These hurdles limit the accessibility many organizations have to NLP capabilities, putting the significant benefits advanced NLP can provide out of reach. *CONFERENCE BREAKOUTS (ON HOPIN.TO PLATFORM) ARE 18TH AND 19TH*Taken from the real-life experiences of our community, the Steering Committee has selected the top applications, achievements and knowledge-areas to highlight.Data November 18th-19th750-950 attendeesWhere? Abstract: Building recommendation systems in production that can serve millions of customers goes way beyond just having a great algorithm. 3. What You Will Learn: In this talk, we will share lessons we learned in answering three questions and the metrics stakeholders care about. 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. Please email info@torontomachinelearning.com. Everyone is welcome. Causal assessments are usually done through A/B tests, which however are not always feasible. 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. Location: San Francisco, California. When will the recordings be available and do I have access to them? Start Date: January 30th, 2020. 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. Despite the vast opportunities that lie within our data, there are also explicit challenges to revealing their potential. 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. I will share some of the technical challenges that we encountered throughout the project and how we overcome them. The failure modes of machine learning systems are also different from those of traditional software applications. The Toronto Machine Learning Summit (TMLS) ... (2020) as an example of a firm that has developed high ROI artificial intelligence applications. As such, more creative thinking is needed to convince stakeholders that your ML solutions can be trusted and bring value. 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. Furthermore, there is a large amount of metadata in the form of actors, ratings, year of release, studio, etc. The special focus will be on artificial intelligence and machine learning … What You Will Learn: Exciting directions and opportunities for assisting machine learning with quantum computers. The huge swathes of data owned by industrial organisations is providing AI and machine learning adopters with limitless opportunities to deliver new products, new business models, and greater insights into their business. Speakers this year include Mastercard, Google, Facebook, Uber, LG, Haliburton, Telus, Sunlife, Uber, KFC, and more!. Start Date: January 30th, 2020. However, in aggregated data environments, confidence in the individual data points varies in a quantifiable manner by primary data source or measurement type. While our delegates will join in from the comfort of their homes and offices across Ireland and around the world, the event itself will be broadcast live from our dedicated studio in Dublin. Paco Nathan, Computer Scientist at Derwen Inc. Abstract: We recently conducted an industry survey of firms that have natural language systems in production. In this talk, I will present some of the challenges in understanding the data and present our platform for content understanding. 15-16 Apr, RE.WORK AI in Retail & Marketing Summit. Some cognitive scientists have proposed that analogy-making is a central mechanism for conceptual abstraction and understanding in humans. We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. Machine Learning; Business. Der ML Summit ist das große Trainingsevent für alle Entwickler:innen, IT-Projektleiter:innen und Product Owner. We will share results demonstrating generalizability towards existing emotion benchmarks from other domains. Abstract: Background: Pricing is a famous business issue in many companies and organizations. Source: Re-Work. These event series bring together the latest technological advancements as well as practical examples to apply AI to solve challenges in business and society. Jose Murillo, Chief Analytics Officer and Francisco Martha Gonzalez, Payments, Digital Banking and IT Managing Director at Banorte. 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. MLOps, Production & Engineering World 2020. 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. Business leaders will learn from the experience of those who have successfully implemented ML/AI and actively manage data teams. The Machine Learning service also has a 3-tier support structure with Data Scientists at L3. 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. 1. Rebecca Knowles, Research Associate at National Research Council of Canada. Q: What's the refund policy? Toronto Machine Learning Summit and Expo 2020 (Virtual) Online event. 5-6 Apr, Middle East Banking AI & Analytics Summit. Toronto Machine Learning Summit (TMLS) — 2018. What You Will Learn: You'll learn how to use software tools like PennyLane, TensorFlow, and PyTorch to train quantum computers, Roxana Barbu, Cognitive Data Specialist at Macadamian Technologies and Scott Plewes, Chief Strategy Officer at Akendi. Eventbrite - Toronto Machine Learning Society (TMLS) presents Toronto Machine Learning 'Micro-Summit' Series ( TMLS) - Finance Special Focus - Wednesday, 15 April 2020 - … Accounting; Business Administration; Human Resources Management; People Analytics; Risk Management; Chartered Business Valuator Program; Marketing, Communications & Design. 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. Taken from the real-life experiences of our community, the Steering Committee has selected the top applications, achievements, and knowledge-areas to highlight. 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. Models degrade and break in production. The NLP Project addressed these challenges by familiarizing industry participants with advanced NLP techniques and the workflows for developing new methods that could achieve high performance while using relatively small data sets and widely accessible computing resources. 2021 dates coming soon! 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. 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. Q: Can my company have a display? Data and AI Summit is Europe's largest data & machine learning conference in the world. 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. What You Will Learn: ML infrastructure and tool stacks are endlessly interesting and convoluted. The 2020 conference will take a special look at the growth of big data and how that will feed machine learning … What You Will Learn: The challenges, the solutions, the effectiveness, and the remaining issues, including technology progress and institutional reform. In addition, the Harvard Business School has written and taught a case study on Jose’s analytics and digital transformation leadership. 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. Abstract: This talk is designed to help you land your first 50 enterprise machine learning customers. 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. 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. 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. #data_science_course Abstract: This talk covers what it means to operationalize ML models. What are key prerequisites to focus yield high ROI on AI projects. 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. These biases may impact the performance of various components of ML systems, from offline training to evaluation and online serving in production systems. Check out who is attending exhibiting speaking schedule & agenda reviews timing entry ticket fees. 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. Abstract: In machine learning, often a tradeoff must be made between accuracy and intelligibility: the most accurate models usually are not very intelligible, and the most intelligible models usually are less accurate.
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