Presentation: DeepRacer and DeepLens, Machine Learning for Fun! (and Profit?)
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In 2017, Amazon announced the DeepLens, a machine learning enabled camera, which they released in 2018. In 2018 they announced the DeepRacer, a 1/8 size model race car that is basically a DeepLens on wheels, which they will release in July. In this talk, you'll hear about the speaker's attempts to do cool things with these machine learning "toys", learn about some of the basics of machine learning necessary to understand what's happening in the devices, and, assuming the device isn't being finicky, see a DeepRacer in action! We will also have a torn down DeepRacer and DeepLens for you to look at and (gently) play with. We'll also go over some possible real life use cases for the devices. Come join us for machine learning fun!
2019 Tracks
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Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
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Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
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Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.
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Predictive Data Pipelines & Architectures
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix
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Sequential Data: Natural Language, Time Series, and Sound
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
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ML in Action
Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud
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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.