Put open source to work
July 16–17, 2018: Training & Tutorials
July 18–19, 2018: Conference
Portland, OR

Artificial intelligence

With the help of open source frameworks, AI is taking software development to a new dimension. How can we utilize data within that development to create smarter “things” and gain insight via machine and deep learning? As AI makes its way throughout industries, hear best practices and ideas on how to create next generation software and businesses outcomes.

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9:00am12:30pm Monday, July 16, 2018
Location: Portland 251
Level: Intermediate
Josh Gordon (Google)
A friendly intro to Deep Learning, taught at the beginner level. We’ll work through exercises across several domains - including computer vision, natural language processing, and structured data classification. We’ll use TensorFlow - the world’s most popular open source machine learning library - preview the latest APIs, discuss best practices, and point you to educational resources to learn more. Read more.
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1:30pm5:00pm Monday, July 16, 2018
Location: Portland 252
Level: Intermediate
Barbara Fusinska (Google)
Natural Language Processing techniques allow addressing tasks like text classification and information extraction and content generation. In this session, Barbara will walk the audience through the process of building the bag of words representation and using it for text classification. The goal of this tutorial is to build the intuition on the simple natural language processing task. Read more.
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9:00am12:30pm Tuesday, July 17, 2018
Location: E143/144
Level: Intermediate
We give an introduction to Deep Learning in Python using Apache MXNet, starting with Deep Learning fundamentals then working through hands-on activities to train and evaluate a model including advanced topics such as training on multiple GPUs. Read more.
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1:30pm5:00pm Tuesday, July 17, 2018
Location: C123-124
Level: Intermediate
Gary Bradski (Stanford | Willow Garage), Anna Petrovicheva (Xperience.ai), Edgar Riba (Universitat Autonoma de Barcelona)
OpenCV (the Open Source Computer Vision Library) version 4.0 is being released this summer. Gary Bradski, Anna Petrovicheva, and Edgar Riba offer an overview of OpenCV and explain where it is going. Along the way, you'll learn how to program some fun things that can be used for art, robotics, drones, film, and photography. Read more.
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1:30pm5:00pm Tuesday, July 17, 2018
Location: E143/144
Level: Beginner
Jonathon Manning (Secret Lab Pty. Ltd.), Tim Nugent (lonely.coffee), Paris Buttfield-Addison (Secret Lab Pty. Ltd.)
Get up to speed with the new machine learning features of iOS. Learn to apply the Vision and Core ML frameworks to solve practical problems in object detection, face recognition, and more. These frameworks run on-device, so they work quickly, with no network access, making them cost-effective and user-privacy conscious. Join in to learn how to build tools that take full advantage of them. Read more.
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11:00am11:40am Wednesday, July 18, 2018
Location: Portland 251
Level: Intermediate
Laurie Hannon (SoftSource Consulting)
Come meet Mycroft, a friend of Siri, Alexa, and (Hey) Google. Like his friends, Mycroft is a virtual assistant. Unlike his friends, Mycroft is entirely open source. See what it takes to code your own custom skill for Mycroft. Hear about how another open source technology, Microsoft’s Bot Framework, can be used for cross-platform chatbots. Get what you need to know to teach Mycroft and friends. Read more.
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11:50am12:30pm Wednesday, July 18, 2018
Location: Portland 251
Level: Intermediate
Joseph Gregorio (Google)
Your continuous integration process produces torrents of data. Come to this session to learn how to mine that data to drive improvements back into your development process. Read more.
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1:45pm2:25pm Wednesday, July 18, 2018
Location: Portland 251
Level: Beginner
Sarah Bird (Facebook)
Earlier this year, Amazon, Facebook and Microsoft partnered together to help advance AI together, by creating ONNX. ONNX stands for Open Neural Network Exchange (ONNX). It is an open format to represent deep learning models. This session will explain in detail how the ONNX framework can help you take AI from research to reality as quickly as possible. Read more.
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2:35pm3:15pm Wednesday, July 18, 2018
Location: Portland 251
Level: Intermediate
Holden Karau (Google)
Tensorflow is all kind of fancy, from helping startups raising their Series A in Silicon Valley to detecting if something is a cat. This talk will explore how Tensorflow can be used in conjunction with Apache Spark, Flink, and BEAM to create a full machine learning pipelines. Read more.
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4:15pm4:55pm Wednesday, July 18, 2018
Location: Portland 251
Level: Intermediate
Van Lindberg (Dykema)
What happens when we apply the latest neural network-based analysis to the nine million patents and patent applications that people have submitted to the USPTO? Not only can we learn new things about what people have invented, we might just be able to get the computer to do a little "inventing" itself. Read more.
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5:05pm5:45pm Wednesday, July 18, 2018
Location: Portland 251
Level: Beginner
Ryan Vanderwerf (Object Computing, Inc), Lee Fox (Infor)
We've developed a 1/16 scale self driving car using Grails Team's new microservice framework the Grails team has developed. This is a port of DonkeyCar project that was leveraged at re:Invent 2017 - a Python based project to use Java and Groovy. We'll show how we built such a thing with this great new technology and show you how we build it. Read more.
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11:00am11:40am Thursday, July 19, 2018
Location: Portland 251
Level: Beginner
Gillian Andrews (ThoughtWorks)
Public concern about the algorithms and data sets shaping our daily lives is growing. Without a Law of Robotics to govern development of artificially intelligent systems, it's up to us to interrogate claims about AI and identify sources of bias. In this session, we'll explore case studies of negative AI impacts on user health, privacy, and reputation, as well as a toolkit to keep them from harm. Read more.
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11:50am12:30pm Thursday, July 19, 2018
Location: Portland 251
Level: Intermediate
Ryan Roser (Thomson Reuters)
In the wake of the financial crisis Thomson Reuters released a novel, text-mining based credit risk model to assess the default risk of publicly traded companies by quantitatively analyzing text. Six years later, we are updating it to use deep learning. This session highlights the benefits and tradeoffs involved in transitioning existing analytics to use deep learning. Read more.
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1:45pm2:25pm Thursday, July 19, 2018
Location: Portland 251
Level: Beginner
Kesha Williams (Chick-fil-A Corporate)
You may not know it, but facial recognition is already a part of our everyday lives. Wherever you go, you are being watched. Facial recognition is integrated with social media, security, gaming, and commerce. Facial recognition technology has the ability to revolutionize the world as we know it. Attend this talk to learn about facial recognition and how to integrate it into your applications. Read more.
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2:35pm3:15pm Thursday, July 19, 2018
Location: Portland 251
Level: Beginner
automagically view the most interesting PlayerUnknown's Battlegrounds streams on Twitch. Read more.
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4:15pm4:55pm Thursday, July 19, 2018
Location: Portland 251
Level: Intermediate
Coraline Ada Ehmke (Stitch Fix)
Introducing Alice, friendly and smart companion for your online community. She's built with a custom natural language processing (NLP) framework, context stacks that track conversation topics, and a pipeline architecture inspired by functional programming. Read more.
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5:05pm5:45pm Thursday, July 19, 2018
Location: Portland 251
Level: Intermediate
Richa Khandelwal explores where engineering fits in machine learning land and shares software engineering and DevOps practices that help in taking a machine learning-powered end-user experience from inception to production. Read more.