Self Aware Streaming
1. Problem Statement
By processing data in motion, Real time/stream processing enables you to get insight into your business and make vital decisions.
Challenges in Stream Processing -
Added by Daljeet Kaur on December 9, 2019 at 2:30am — No Comments
Why would a data scientist use Kafka Jupyter Python KSQL TensorFlow all together in a single notebook?
There is an impedance mismatch between model development using Python and its Machine Learning tool stack and a scalable, reliable data platform. The former is what you need for quick and easy prototyping to build analytic models. The latter is what you need to use for data ingestion, preprocessing, model deployment and monitoring at scale. It…Continue
Added by Kai Waehner on January 22, 2019 at 10:00am — No Comments
I built a scenario for a hybrid machine learning infrastructure leveraging Apache Kafka as scalable central nervous system. The public cloud is used for training analytic models at extreme scale (e.g. using TensorFlow and TPUs on Google Cloud Platform (GCP) via Google ML Engine. The predictions (i.e.…Continue
Machine Learning / Deep Learning models can be used in different ways to do predictions. My preferred way is to deploy an analytic model directly into a stream processing application (like Kafka Streams or KSQL). You could e.g. use the …Continue
Added by Kai Waehner on July 8, 2018 at 4:26pm — No Comments
I had a new talk presented at "Codemotion Amsterdam 2018" this week. I discussed the relation of Apache Kafka and Machine Learning to build a Machine Learning infrastructure for extreme scale.
Long version of the title:
"Deep Learning at Extreme Scale (in the Cloud) with the Apache Kafka Open Source Ecosystem - How to Build a Machine Learning Infrastructure with Kafka, Connect, Streams, KSQL, etc."
As always, I want to share the slide deck. The talk was…Continue
Added by Kai Waehner on May 8, 2018 at 9:30pm — No Comments
Summary: This is the first in a series of articles aimed at providing a complete foundation and broad understanding of the technical issues surrounding an IoT or streaming system so that the reader can make intelligent decisions and ask informed questions when planning their IoT system.
In This Article…