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Machine learning on real-time data is a powerful combination because you gain direct insights into your data, can make powerful decisions, and consequently improve your business processes and outcomes. It […]
Imagine you’ve been working with Confluent and just got your new streaming pipeline set up to power your new predictive maintenance solution. Next, you look to implement machine learning (ML) […]
This blog post shows how transactional machine learning (TML) integrates data streams with automated machine learning (AutoML), using Apache Kafka® as the data backbone, to create a frictionless machine learning […]
Twitter, one of the most popular social media platforms today, is well known for its ever-changing environment—user behaviors evolve quickly; trends are dynamic and versatile; and special and emergent events […]
Mainframes are still ubiquitous, used for almost every financial transaction around the world—credit card transactions, billing, payroll, etc. You might think that working on mainframe software would be dull, requiring […]
We talked about how easy it is to send osquery logs to the Confluent Platform in part 1. Now, we’ll consume streams of osquery logs, detect anomalous behavior using machine […]
The combination of streaming machine learning (ML) and Confluent Tiered Storage enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache […]
The relationship between Apache Kafka® and machine learning (ML) is an interesting one that I’ve written about quite a bit in How to Build and Deploy Scalable Machine Learning in […]
We recently launched a new artificial intelligence (AI) data extraction API called Scrapinghub AutoExtract, which turns article and product pages into structured data. At Scrapinghub, we specialize in web data […]
Have you ever realized that, according to the latest FBI report, more than 80% of all crimes are property crimes, such as burglaries? And that the FBI clearance figures indicate […]
Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine […]
Machine learning and the Apache Kafka® ecosystem are a great combination for training and deploying analytic models at scale. I had previously discussed potential use cases and architectures for machine […]
Kafka Streams makes it easy to write scalable, fault-tolerant, and real-time production apps and microservices. This post builds upon a previous post that covered scalable machine learning with Apache Kafka, […]
Scalable Machine Learning in Production with Apache Kafka® Intelligent real time applications are a game changer in any industry. Machine learning and its sub-topic, deep learning, are gaining momentum because […]