Presented By O’Reilly and Intel Nervana
Put AI to work
September 17-18, 2017: Training
September 18-20, 2017: Tutorials & Conference
San Francisco, CA

Tutorials

On Monday, September 18, choose from the following half-day tutorials. These expert-led presentations give you a chance to dive deep into the subject matter. Please note: to attend, your registration package must include tutorials on Monday; does not include access to training courses.

Monday, September 18

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9:00am–12:30pm Monday, September 18, 2017
Location: Yosemite A Level: Advanced
Secondary topics:  Data science and AI
Average rating: ****.
(4.75, 4 ratings)
Probabilistic inference, a widely used, mathematically rigorous approach for interpreting ambiguous information using models that are uncertain or incomplete, is central to everything from big data analytics to robotics and AI. Vikash Mansinghka surveys the emerging field of probabilistic programming, which aims to make modeling and inference broadly accessible to nonexperts. Read more.
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9:00am–12:30pm Monday, September 18, 2017
Location: Imperial A Level: Intermediate
Secondary topics:  Deep learning, Tools and frameworks
Yufeng Guo (Google), Amy Unruh (Google)
Average rating: ***..
(3.33, 6 ratings)
Yufeng Guo and Amy Unruh walk you through training and deploying a machine learning system using TensorFlow, a popular open source library. Yufeng and Amy take you from conceptual overviews all the way to building complex classifiers and explain how you can apply deep learning to complex problems in science and industry. Read more.
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9:00am–12:30pm Monday, September 18, 2017
Location: Nob Hill 2 & 3 Level: Intermediate
Secondary topics:  Algorithms, Case studies
Bruno Gonçalves (New York University)
Average rating: ****.
(4.50, 2 ratings)
Bruno Gonçalves explores word2vec and its variations, discussing the main concepts and algorithms behind the neural network architecture used in word2vec and the word2vec reference implementation in TensorFlow. Bruno then presents a bird's-eye view of the emerging field of "anything"-2vec methods that use variations of the word2vec neural network architecture. Read more.
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9:00am–12:30pm Monday, September 18, 2017
Location: Yosemite BC Level: Intermediate
Secondary topics:  Algorithms, Data science and AI, Transportation and autonomous vehicles
Marcos Campos (Bonsai)
Average rating: **...
(2.33, 9 ratings)
Marcos Campos offers an overview of reinforcement learning, walking you through the various classes of reinforcement learning algorithms, the types of problems that can be solved with this technique, and how to build and train AI models using reinforcement learning and reward functions. Read more.
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9:00am–12:30pm Monday, September 18, 2017
Location: Imperial B Level: Intermediate
Secondary topics:  Case studies, Enterprise adoption
Jana Eggers (Nara Logics)
Average rating: ***..
(3.43, 14 ratings)
Now is the time for us to define roles and capabilities for AI in business. Jana Eggers demonstrates how to deliver on an AI project for business, walking you through defining your project, setting expectations, assembling your team, hunting for data, assessing capabilities, implementing it, and rinsing and repeating. Read more.
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1:30pm–5:00pm Monday, September 18, 2017
Location: Imperial B Level: Non-technical
Secondary topics:  Enterprise adoption, Tools and frameworks
Kristian Hammond (Narrative Science)
Average rating: ****.
(4.68, 22 ratings)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Kristian Hammond shares a practical framework for understanding the role of AI technologies in problem solving and decision making. Read more.
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1:30pm–5:00pm Monday, September 18, 2017
Location: Yosemite A Level: Advanced
Secondary topics:  Data science and AI, Tools and frameworks
Gunnar Carlsson (Ayasdi)
Average rating: *****
(5.00, 1 rating)
Topological data analysis (TDA) is a framework for machine learning that synthesizes and combines machine learning algorithms to identify the shape of data. The technique is responsible for several major breakthroughs in our understanding of science and business. Gunnar Carlsson offers an overview of TDA's mathematical underpinnings and its practical application through software. Read more.
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1:30pm–5:00pm Monday, September 18, 2017
Location: Yosemite BC Level: Intermediate
Secondary topics:  Data and training, Transportation and autonomous vehicles
Mo Patel (Independent), Laura Froelich (Think Big Analytics, a Teradata Company)
Average rating: **...
(2.00, 3 ratings)
Computer vision is a key component in the artificial intelligence revolution. Assisted by deep learning, object detection allows automotive applications to make key navigation, guidance, and driving decisions to avoid collisions and navigation errors. Laura Froelich and Mo Patel demonstrate how to train deep learning models for object detection using publicly available transportation datasets. Read more.
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1:30pm–5:00pm Monday, September 18, 2017
Location: Imperial A Level: Intermediate
Secondary topics:  Algorithms, Open source, Transportation and autonomous vehicles
Ion Stoica (UC Berkeley), Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley)
Average rating: ****.
(4.57, 7 ratings)
Ion Stoica, Robert Nishihara, and Philipp Moritz lead a deep dive into Ray, a new distributed execution framework for reinforcement learning applications, walking you through Ray's API and system architecture and sharing application examples, including several state-of-the art RL algorithms. Read more.