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What Came First: The Ordering of Events in Systems
Kavya Joshi explores the beautifully simple happens-before principle and delves into how happens-before is tracked in a distributed database like Riak.
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Automating Inventory at Stitch Fix
Sally Langford talks about the use of ML within StitchFix’s inventory forecasting system, the architecture they have developed in-house and their use of Bayesian methods.
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Solving Payment Fraud and User Security with ML
Soups Ranjan talks about Coinbase’s risk program that relies on machine learning (supervised and unsupervised), rules-based systems as well as highly-skilled human fraud fighters.
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Evaluating Machine Learning Models: A Case Study
Nelson Ray talks about on how to estimate the business impact of launching various machine learning models, in particular, those Opendoor uses for modeling the liquidity of houses.
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Deep Learning @Google Scale: Smart Reply in Inbox
Anjuli Kannan describes the algorithmic, scaling, deployment considerations involved in a an application of cutting-edge deep learning in a user-facing product: the Smart Reply feature of Google Inbox
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Semi-Supervised Deep Learning on Large Scale Climate Models
Prabhat presents NERSc’s results in applying Deep Learning for supervised and semi-supervised learning of extreme weather patterns, scaling Deep Learning to 9000 KNL nodes on a supercomputer.
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API Design Lessons Learned: Enterprise to Startup
Mohamed El-Geish explores lessons learned at big companies like Microsoft and LinkedIn, and adapts the insights drawn from them to fit a fast-growing startup.
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Beyond REST: Coursera's Journey to GraphQL
Bryan Kane talks about why Coursera is transitioning to GraphQL and shares challenges and learnings from building their GraphQL assembly layer.
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Rethinking CodeGen: IDL, Thrift, gRPC, Ohh My
Cameron Waeland discusses the evolution of Compass and presents their extensible code generation framework which is at the heart of their automatically generated REST to gRPC reverse proxy.
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Hardware & Provisioning Engineering @Twitter
M. Singer and N. Johnson present the Provisioning Engineering system at Twitter, called Wilson, which together with Audubon is designed to handle every part of a server's lifecycle.
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Front-End APIs: Powering Fast-Paced Iterations
Aditya Modi and Karthik Ramgopal explore LinkedIn’s ideas behind API modeling, the challenges they’ve faced, and how they are evolving their modeling strategy over time based on their learnings.
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Generating Unified APIs with Protocol Buffers and gRPC
Chris Roche and Christopher Burnett discuss how they extended the Protocol Buffer (PB) IDL to create unified APIs and data models, and how they used Envoy to move HTTP 1.1 services to gRPC.
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