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Scale By the Bay 2018
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Popular Events on Friday, November 16
#1
Keynote II: Kafka and the Rise of Event-Driven Microservices
#2
How Twitter teaches Scala
#3
Using Akka Streams for Web-scale Data Ingestion
#4
Panel II: Data Engineering and AI
#5
Fast Data pipelines with Akka Streams and Alpakka Kafka Connector
#6
Breakfast and Welcome
#7
Rust and Other Interesting Things
#8
Concurrency with Cats-effect
#9
Lunch
#10
Swimming in the stream: A simple data analytics pipeline with Akka Streams
#11
Enabling Big Data and Machine Learning for the Masses: Creating a Spark Platform for the Uninitiated
#12
Getting started with EitherT
#13
Declarative distributed concurrency in Scala
#14
Stream Processing at Lyft with Flink and Beam
#15
Graph-First Services Using GraphQL
#16
Scaling Bayesian Experimentation
#17
Play on Dotty: Design Patterns unlocked by Dotty in a Play look-alike demo project
#18
High-performance functional bayesian inference in Scala
#19
Distinguishing features of production-quality data pipelines
#20
Nelson: Functional programming in system design
#21
Orchestrating Microservices with GraphQL
#22
Scalaz Stream: Rebirth
#23
Happy Hour II
#24
Towards Typesafe Deep Learning in Scala
#25
Data Consistency Patterns in Cloud Native Applications
#26
FiloDB: Real-time, In-Memory Time Series at Massive SMACK Scale
#27
Adopting GraalVM
#28
You Are a Scala Contributor
#29
Scala the Cloud Native Way: Lessons Learned from Two Years of Linkerd in Production
#30
Scio data processing nirvana at Spotify
#31
Fireside Chat with Richard Socher, Chief Scientist, Salesforce
#32
Structured Deep Learning with Probabilistic Neural Programs
#33
Building a Contacts Graph from activity data
#34
5 tips to build long-lasting Scala OSS
#35
Optimizing network topologies with monadic execution contexts
#36
Distributed Deep Learning with Horovod
#37
Labels to Inference: A Continuous Sentiment Pipeline
#38
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