Apache Kafka and Machine Learning in Banking and Finance Industry
The combination of Apache Kafka and Machine Learning / Deep Learning are the new black in Banking and…
Browsing Tag
Real Time
17 posts
Smart City with an Event Streaming Platform like Apache Kafka
A smart city is an urban area that uses different types of electronic Internet of Things (IoT) sensors…
Streaming Machine Learning with Apache Kafka, Tiered Storage, TensorFlow
The combination of streaming machine learning (ML), Apache Kafka and Confluent Tiered Storage enables you to build one…
The Rise Of Event Streaming – Why Apache Kafka Changes Everything
I had the pleasure to deliver the keynote at OOP 2020 in Munich, Germany. This is a well-known…
Apache Kafka is the New Black at the Edge in Industrial IoT, Logistics and Retailing
The following question comes up almost every week in conversations with customers: Can and should I deploy Apache…
Apache Kafka in the Automotive Industry
In November 2019, I had the pleasure to visit “Motor City” Detroit. I met with several automotive companies,…
IoT Live Demo – 100.000 Connected Cars with Kubernetes, Kafka, MQTT, TensorFlow
Live Demo – 100.000 Connected Cars – Real Time Processing and Analytics with Kubernetes, Kafka, MQTT and TensorFlow leveraging Confluent and HiveMQ.
Deep Learning in Real Time with TensorFlow, H2O.ai and Kafka Streams (Slides from JavaOne 2017)
Apache Kafka + Kafka Streams to Produductionize Neural Networks (Deep Learning). Models built with TensorFlow, DeepLearning4J, H2O. Slides from JavaOne 2017.
Apache Kafka Streams + Machine Learning (Spark, TensorFlow, H2O.ai)
Apache Kafka Streams to build Real Time Streaming Microservices. Apply Machine Learning / Deep Learning using Spark, TensorFlow, H2O.ai, etc. to add AI. Embed Kafka Streams into Java App, Docker, Kubernetes, Mesos, anything else.
Comparison: Data Preparation vs. Inline Data Wrangling in Machine Learning and Deep Learning Projects
Data Preparation: Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling in Machine Learning / Deep Learning Projects.
