Marko Topolnik, PhD, has been a Java professional since 2001. His current position is in the core team of Hazelcast Jet, where he co-wrote the core execution engine based on coroutine-like suspendable code that runs many concurrent tasks on a fixed thread pool. Marko is also an active contributor on Stack Overflow, on the kotlin-coroutines tag.
Real-Time Streaming with Python ML Inference
The capabilities of machine learning are now pretty well understood and there are great tools to do data science and construct models that answer nontrivial questions about your data. These tools are often used from Python.
The key new challenge is making the trained prediction model usable in real time, while the user is interacting with your software. Getting answers from an ML model takes a lot of CPU/GPU and must be done at serious scale. The ML tools are optimized mainly for batch-processing a lot of data at once, and often the implementations aren’t parallelized.
In this talk Marko will show one approach which allows you to write a low-latency, auto-parallelized and distributed stream processing pipeline in Java that seamlessly integrates with a data scientist’s work taken in almost unchanged form from their Python development environment.
The talk includes a live demo using the command line and going through some Python and Java code snippets.