Speaker: Tyler Akidau
Tyler Akidau is a senior staff software engineer at Google, where he is the technical lead for the Data Processing Languages & Systems group, responsible for Google's Apache Beam efforts, Google Cloud Dataflow, and internal data processing tools like Google Flume, MapReduce, and MillWheel. His also a founding member of the Apache Beam PMC. Though deeply passionate and vocal about the capabilities and importance of stream processing, he is a firm believer in batch and streaming as two sides of the same coin, with the real endgame for data processing systems the seamless merging between the two. He is the author of the 2015 Dataflow Model paper, the Streaming 101 and Streaming 102 articles, and the upcoming Streaming Systems book. His preferred mode of transportation is by cargo bike, with his two young daughters in tow.
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2019 Tracks
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Groking Timeseries & Sequential Data
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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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.
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AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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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.