Over 100,000 organizations use Apache Kafka for data streaming. However, there is a problem: The broad ecosystem lacks a mature client framework and managed cloud service for Python data engineers. Quix Streams is a new technology on the market trying to close this gap. This blog post discusses this Python library, its place in the Kafka ecosystem, and when to use it instead of Apache Flink or other Python- or SQL-based substitutes.
IT modernization and innovative new technologies change the healthcare industry significantly. This blog series explores how data streaming with Apache Kafka enables real-time data processing and business process automation. Real-world examples show how traditional enterprises and startups increase efficiency, reduce cost, and improve the human experience across the healthcare value chain, including pharma, insurance, providers, retail, and manufacturing. This is part five: Open API and Omnichannel. Examples include Care.com and Invitae.
Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural…
Data Preparation: Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling in Machine Learning / Deep Learning Projects.