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"bio" : "Slava Nikitin is a data scientist at the Columbus Collaboratory. He mixes statistical and computational ideas to build automated inference systems across 7 industry verticals that make up the Collaboratory. Outside of Collaboratory, he teaches a data analytics course at the Otterbein University Business School, sharing the modern data technology stack and how it can be used to create new businesses, or transform existing ones.",
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"description" : "Let your users be the voice talent with Actions on Google. Learn how to design, develop, and distribute rich conversational experiences with Node.js. We’ll show you how to approach voice-driven, natural language interactions with Dialogflow’s powerful bot platform.",
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"description" : "Immersive virtual reality (VR), augmented reality (AR), and mixed reality (MR) are becoming mainstream while their software and hardware are rapidly changing. They introduce new and novel usability issues ranging from high-level project methodology down to detailed design of sensory elements in their user interfaces. They also sometimes affect non-users who are interacting with AR and MR users. Key questions include defining (a) new usability-design strategies and (b) new procedures and processes for usability testing. The Five-Finger project life cycle and the GAINS™ design framework provide an approach to answering these questions and designing excellent user interfaces.",
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"speakers" : [ 10 ],
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"speakers" : [ 5 ],
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"complexity" : "Beginner",
"description" : "Android TV’s home screen has received a makeover with Android Oreo. With this update, users can decide what to watch from multiple apps at once from the home screen. In addition, the Google Assistant is also available for users to discover and control playback of content on their Android TV. We will look at how to surface your app’s content on the home screen by creating channels. We will also examine how to integrate your app with the Google Assistant with MediaSession. ",
"id" : 104,
"speakers" : [ 2 ],
"tags" : [ "TV", "Android" ],
"title" : "Android TV's new home screen"
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"description" : "Kotlin has a lot of great features that improve developer productivity and make the overall code base more stable. This all works great when you're entire code base is written in Kotlin. However, while Kotlin adoption is growing by leaps and bounds, the fact is that many applications and libraries are still on Java and will be for some time. This means, if you're a library provider like Realm that 100k+ developers rely on, you must provide an API that works well for both platforms. In this talk, you'll learn about some of the challenges faced and approaches taken by Realm to solve this problem and how you might apply these same approaches to your own libraries. You'll also learn about some of the key Kotlin features they used to simplify Realm Mobile Database development with Kotlin.",
"id" : 105,
"speakers" : [ 4 ],
"tags" : [ "Kotlin", "Android", "Realm" ],
"title" : "Building Libraries for Kotlin"
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"106" : {
"complexity" : "Intermediate",
"description" : "Lombok, Retrofit, Dagger. These project all have one thing in common; they all use Java's annotation API. Many developers look at these libraries as black magic which is effective but inscrutable. No more! In this session developers will learn how they can create their own annotation library in order to reduce boilerplate code and improve the lives of their fellow developers. We'll shed light on how to create annotations, how to parse the AST using the AbstractProcessor, and how to generate code using the JavaPoet library. By the end of this session developers will come away with a better understanding of how annotations work and how they can create them themselves.",
"id" : 106,
"speakers" : [ 6 ],
"tags" : [ "Java", "Annotations", "AST" ],
"title" : "Annotation Processing - Demystifying Java's Dark Arts"
},
"107" : {
"complexity" : "Beginner",
"description" : "This talk will provide a broad overview of some of the most popular machine learning algorithms and techniques. Specific topics may include Decision Trees, Random Forests, Neural Networks, and associated ensemble methods (gradient boosting vs. bagging/bootstrapping). Attendees can expect a high-level overview of techniques, a review of the circumstances under which they are and aren't appropriate for use, and a brief crash course on how to implement some popular algorithms using open source software.",
"id" : 107,
"speakers" : [ 8 ],
"tags" : [ "Machine Learning" ],
"title" : "Using Popular Machine Learning Models and Techniques"
},
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"complexity" : "Intermediate",
"description" : "AI powered software is showing huge growth. What is it, how is it built and what is special about it? This talk will provide a perspective on these questions starting with the idea of AI as automated inference. The story will involve theories of probability and statistics, design space of inference systems, their pros and cons, probabilistic programming, hardware accelerators, data, with examples tying the different points together. Overall, the proposed perspective, powered by a certain stack of hardware and software, provide a powerful framework for solving many interesting and valuable problems.",
"id" : 108,
"speakers" : [ 14 ],
"tags" : [ "Machine Learning", "AI", "Data Science" ],
"title" : "AI is Automated Inference -- AI is eating software while Software is eating the world"
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"complexity" : "Beginner",
"description" : "Currently, we are in the wave of IoT data collection. We are figuring out ways to attach microchips and sensors to everything to collect as much data possible -- this is solely for one purpose: Machine Learning. The next big part of IoT is learning from all the information we can collect. This talk will cover the process of collecting data from hardware and using TensorFlow to predict future values. With this foundation, one can use these same learnings to build more complex ML & IoT solutions. ",
"id" : 109,
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