Scale By the Bay 2018 has ended

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Scale By the Bay 2018

ZW

Zhaoting Wu

Credit Karma
Software Engineer

8:00am PST

Breakfast and Welcome Commons

8:45am PST

Grand Welcome and Opening Remarks functional

9:00am PST

Opening Keynote: New Functional Constructs in Scala 3 functional

9:50am PST

ArrayDeques and How to Contribute to Scala 2.13 Collections functional

10:40am PST

FP for Data Science: For-Loops Considered Harmful data

11:10am PST

Making Spark ML Models Portable - Know Your Options data The Danger of Implicit Blocking in Finagle reactive

11:40am PST

From Scala to ByteCode — a view of how Scala is implemented on top the JVM. functional

12:20pm PST

1:10pm PST

Monitoring AI with AI data

1:40pm PST

Video Access-Log Processing with Apache Flink data

2:10pm PST

Evolution of GoPro's Data Platform data

3:00pm PST

Consensus Algorithms in Distributed Systems reactive

3:45pm PST

Machine Learning on Source Code data

4:25pm PST

Inside NVIDIA’s AI infrastructure for self-driving cars data

5:10pm PST

Panel I: Thoughtful Software Engineering functional

6:00pm PST

Happy Hour I Commons

8:00am PST

Breakfast and Welcome Commons

9:00am PST

Keynote II: Kafka and the Rise of Event-Driven Microservices functional

9:50am PST

Fast Data pipelines with Akka Streams and Alpakka Kafka Connector reactive

10:40am PST

Swimming in the stream: A simple data analytics pipeline with Akka Streams reactive

11:10am PST

Towards Typesafe Deep Learning in Scala data

11:30am PST

Using Akka Streams for Web-scale Data Ingestion reactive

11:50am PST

Enabling Big Data and Machine Learning for the Masses: Creating a Spark Platform for the Uninitiated data

12:00pm PST

Scaling Bayesian Experimentation reactive

12:30pm PST

1:10pm PST

Getting started with EitherT functional

1:40pm PST

Distinguishing features of production-quality data pipelines reactive

2:10pm PST

Nelson: Functional programming in system design reactive

3:00pm PST

Scala the Cloud Native Way: Lessons Learned from Two Years of Linkerd in Production reactive

3:30pm PST

Scio data processing nirvana at Spotify data

3:40pm PST

Concurrency with Cats-effect functional

3:55pm PST

Data Consistency Patterns in Cloud Native Applications reactive

4:30pm PST

Distributed Deep Learning with Horovod data Stream Processing at Lyft with Flink and Beam reactive

5:10pm PST

Panel II: Data Engineering and AI functional

6:00pm PST

Happy Hour II Commons

8:00am PST

Breakfast and Welcome Commons

9:00am PST

Keynote III: Mind Your State for Your State of Mind functional

9:50am PST

Introduction to Apache Spark with Frameless data

10:40am PST

Motivating Probabilistic Programming data Structure and Interpretation of Stream Processing reactive

11:10am PST

Applied Machine Learning: a Netflix production data

11:40am PST

Hadoop Future in AI World data

12:20pm PST

1:10pm PST

Quantum Computing Modeling in Scala reactive

1:40pm PST

Journey of Building a Modern Data Prep Tool on Top of Apache Spark reactive

2:10pm PST

Adding Custom Optimizations to Catalyst by Example with the DSE Spark Connector data Deploying Kafka Streams Applications with Docker and Kubernetes reactive

3:00pm PST

MLflow: An open platform to simplify the machine learning lifecycle data

3:45pm PST

Effects types in Scala - how to choose one functional

4:25pm PST

Reactive Microservice framework for Realtime Model Executions reactive

5:10pm PST

Panel III: Cloud, Edge, and Silver Lining functional