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Your Guide to AI and Machine Learning at re:Invent 2018 Amazon Web Services

#artificialintelligence

As you plan your agenda, artificial intelligence (AI) is undoubtedly a hot topic on your list. This year we have a lot of great technical content on AI, machine learning (ML), and deep learning (DL)--with over 200 breakout sessions, hands-on workshops, deep-dive chalk talks, and more. You'll hear success stories about machine learning on AWS firsthand from customers and partners such as Sony, Moody's, NFL, Intuit, 21st Century Fox, Toyota, and more. This year's re:Invent also includes the AI Summit, where thought leaders in the academic community will share their perspectives on the future of AI. Here are a few highlights of this year's lineup from the re:Invent session catalog to help you plan your event agenda.


Your guide to artificial Intelligence and machine learning at re:Invent 2019 Amazon Web Services

#artificialintelligence

With less than 40 days to re:Invent 2019, the excitement is building up and we are looking forward to seeing you all soon! Continuing our journey on artificial intelligence and machine learning, we are bringing a lot of technical content this year, with over 200 breakout sessions, deep-dive chalk talks, hands-on exercises with workshops featuring Amazon SageMaker, AWS DeepRacer, and deep learning frameworks such as TensorFlow, PyTorch, and more. You'll hear from many customers including Vanguard, BBC, Autodesk, British Airways, Fannie Mae, Thermo Fisher, Intuit, and many more. We are also hosting the Machine Learning Summit again this year, where you will hear from researchers and entrepreneurs about the latest breakthroughs today and the future possibilities tomorrow. To get you started on planning, here are a few highlights for the AI and ML sessions from the re:Invent 2019 session catalog.


What Deep Learning has to Offer to the Future of Online Personalization

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Huba Gaspar, Global Marketing Manager at Gravity R&D outlines one of the hottest tech buzzwords Deep Learning (DL) and possible ways in which DL based approaches can revolutionize personalization technologies. Deep learning is a sub-field of machine learning and it comprises several approaches to tackling the single most important goal of AI research: allowing computers to model our world well enough to exhibit something like what we humans call intelligence. On a basic conceptual level, deep learning approaches share a very basic trait. DL algorithms interpret the raw data through multiple processing layers. Each of these layers takes the output of the previous one as its input and creates a more abstract representation of it.


Knowledge Discovery in Databases: An Overview

AI Magazine

After a decade of fundamental interdisciplinary research in machine learning, the spadework in this field has been done; the 1990s should see the widespread exploitation of knowledge discovery as an aid to assembling knowledge bases. The contributors to the AAAI Press book Knowledge Discovery in Databases were excited at the potential benefits of this research. The editors hope that some of this excitement will communicate itself to "AI Magazine readers of this article.


How Deep Learning is Personalizing the Internet - Dataconomy

#artificialintelligence

Deep learning is a subfield of machine learning and it comprises several approaches to tackling the single most important goal of AI research: allowing computers to model our world well enough to exhibit something like what we humans call intelligence. On a basic conceptual level, deep learning approaches share a very basic trait. DL algorithms interpret the raw data through multiple processing layers. Each of these layers takes the output of the previous one as its input and creates a more abstract representation of it. As a result, the more data is being fed into the right algorithm, the more general are the rules and features that it's able to infer in relation to a given scenario and, therefore, the apter it gets at handling new, similar situations.