Tech Talk: Machine Learning at Scale using distributed stream processing

In this video, Marko Topolnik shows one practical approach which allows you to write a low-latency, auto-parallelised and distributed stream processing pipeline (Java), using a model developed in Python.

About this course

How to make a trained prediction model usable in real time, while the user is interacting with your software. Going from fast trial-and-error runs on historical data to models that perform at production scale, in real time. In this talk Marko Topolnik shows one practical approach which allows you to write a low-latency, auto-parallelised and distributed stream processing pipeline (Java), using a model developed in Python.

About this course

How to make a trained prediction model usable in real time, while the user is interacting with your software. Going from fast trial-and-error runs on historical data to models that perform at production scale, in real time. In this talk Marko Topolnik shows one practical approach which allows you to write a low-latency, auto-parallelised and distributed stream processing pipeline (Java), using a model developed in Python.