I spent most of my adult life trying to build reusable code in imperative languages before realizing I was building castles in sand. I converted to Haskell in 2006 while searching for better building materials. I now chair the Haskell core libraries committee, collaborate with hundreds of other developers on over 200 projects on github, build tools for quants and traders using the purely-functional programming-language Ermine I designed for S&P Capital IQ, and I am obsessed with finding better tools so that seven years from now I won’t be stuck solving the same problems with the same tools I was stuck using seven years ago.
Architecting Typed FP Applications & Libraries in Kotlin with Λrrow
In this talk we will learn the fundamentals of Typed Functional Programming applied to Kotlin with the library Arrow and how we can architect applications and libraries that are polymorphic and composed of pure abstract functions using type classes. Arrow provides a unified programming model in by which Kotlin practitioners can build programs relying on the traditional FP, MTL and Effect type classes in a Tagless Final style offering levels of flexibility and techniques new to the Kotlin FP community.
Co-Author and maintainer of Λrrow, Freestyle and other FP libs in the Scala and Kotlin communities. CTO @47deg, Optimistic.
Bringing the Jewels of the Python world to Scala with Spark
With the new Apache Arrow integration in PySpark 2.3, it is now starting become reasonable to look to the Python world and ask “what else do we want to steal besides tensorflow”, or as a Python developer look and say “how can I get my code into production without it being rewritten into a mess of Java?”. Regardless of your specific side(s) in the JVM/Python divide, collaboration is getting a lot faster, so lets learn how to share! In this brief talk we will examine sharing some of the wonders of Spacy with the JVM world, which still has a somewhat lackluster set of options for NLP & deep learning.
Holden Karau Open Source Big Data Developer Advocate, Google
Holden is a transgender Canadian open source developer advocate @ Google with a focus on Apache Spark, BEAM, and related 'big data' tools. She is the co-author of Learning Spark, High Performance Spark, and another Spark book that's a bit more out of date. She is a commiter on and PMC on Apache Spark and committer on SystemML & Mahout projects. She was tricked into the world of big data while trying to improve search and recommendation systems and has long since forgotten her original goal.