Scala collections 101 and beyond-AND-Real-time machine learn' using Apache Flink

• Kurics Tamás (Twinner) - Scala collections 101 and beyond - using Scala in (not just) competitive programming:
  Everyone who starts to learn Scala encounters with the most fundamental and ubiquitous linear data structure present in all functional languages, the linked list, or simply just list.
  Many methods defined in the List trait can be implemented by using the 3 main building blocks only: isEmpty, head and tail. It is always a good exercise to implement
  other methods such as take, drop and many more by using these building blocks that work very efficiently for Lists. But what about other collections? What these methods mean for Vectors,
  Strings, Arrays and other structures defined in the Scala collections library? Are they just as efficient as for Lists? Scala is a language shipped with a very rich set of collections,
  and when it comes to performance, it really does matter which one is selected for a particular task. The topic of this talk has arisen from my experiences in solving Hackerrank problems
  and rewriting anomaly detection and biometric algorithms from Python to Scala for a user behaviour analytics software at Balabit.

• Berecz Dániel (Ekata) - Parameter Server on Flink, an approach for model-parallel machine learning:
  In this talk, we show a Parameter Server implementation in Flink for model-parallel machine learning. To scale efficiently, some machine learning algorithms not only require the input to be processed in parallel but to train and store the model in a distributed manner. The Parameter Server provides an abstraction layer for the distributed model, so the implementation of such algorithms is much easier. We present how our Parameter Server can be used for model-parallel training in Flink through recommendation with matrix factorization. Our implementation is built entirely on top of the Streaming API, so Flink can also be used to preprocess the data and even to serve predictions in a single job.

17:45 Doors open: introductions, networking
18:00 Scala collections 101 and beyond - using Scala in (not just)
competitive programming
18:40 Break: networking, drinks
18:50 Parameter Server on Flink, an approach for model-parallel machine learning
19:30 Networking, pizza, drinks
20:00 We continue to Gold Biliárd

Both presentations' languages are optional, depends on the audience: English or Hungarian

Pizza and beverages will be served after the presentations.