InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Back to the Future: Demystifying Hindsight Bias
Enterprise AI has more prevalent nuances in the input data than in consumer AI or academia. The Achilles’ heel in this domain is Hindsight Bias. In layman terms, it is like Marty McFly (from Back to the Future) traveling to the future, getting his hands on the Sports Almanac, and using it to bet on the games of the present. Mayukh Bhaowal from Salesforce Einstein explains how to counteract it.
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Q&A on the Book Software Wasteland
Almost all Enterprise Information Systems now cost vastly more to implement than they should. When you have hundreds or thousands of complex applications, you are stuck in the Application Centric Quagmire. In the book Software Wasteland Dave McComb explores what is causing application development waste and how visualizing the cost of change and becoming data-centric can help to reduce the waste.
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Virtual Panel: Microservices Communication and Governance Using Service Mesh
Service mesh is a dedicated infrastructure layer for handling service-to-service communication and offers a platform to connect, manage, and secure microservices. InfoQ spoke with subject matter experts in the service mesh area to learn more about why service mesh frameworks have become critical components of cloud native architectures.
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Polyglot Persistence Powering Microservices
At Netflix, the cloud database engineering team is responsible for providing several flavors of data persistence as a service to microservice development teams. Roopa Tangirala explained how her team has created self-service tools that help developers easily implement the appropriate data store for each project's needs.
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Migrating Batch ETL to Stream Processing: A Netflix Case Study with Kafka and Flink
At QCon New York, Shriya Arora presented “Personalising Netflix with Streaming Datasets” and discussed the trials and tribulations of a recent migration of a Netflix data processing job from the traditional approach of batch-style ETL to stream processing using Apache Flink.
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Exploring the Fundamentals of Stream Processing with the Dataflow Model and Apache Beam
At QCon San Francisco 2016, Frances Perry and Tyler Akidau presented “Fundamentals of Stream Processing with Apache Beam”, and discussed Google's Dataflow model and associated implementation of Apache Beam.
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Playing with Messaging Chatbots in the Omnichannel Contact Center
The proliferation of messaging platforms is forcing companies to shift towards an omnichannel strategy, where they need to be able to contact people in their preferred channel. In this article we will develop an omnichannel messaging chatbot that offers two-way communications over SMS and Facebook using the Twilio Studio visual tool.
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JPA 2.2 Brings Some Highly Anticipated Changes
Released this past summer, JPA 2.2 delivered some frequently requested enhancements, especially by providing better alignment with Java 8 features, such as support for the Date and Time API and the retrieval of a query result as a Stream.
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Get More Bytes for Your Buck
Lovethesales had to classify one million product data from 700 different disparate sources across a large domain. They decided to create a hierarchy of classifiers through utilizing machine learning, specifically Support Vector Machines. They learned that optimising the way in which the svms were connected together yielded vast improvements in the reuse of labeled training data.
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Approximate Queries on WSO2 Stream Processor: Use of Approximation Algorithms in an Applied Setting
In this article, we describe an example real world application of API monitoring which benefits from using approximate stream processing. We developed the application on top of WSO2 Stream Processor as Siddhi extension. Siddhi is the complex event processing library which acts as the event processing engine of WSO2 Stream Processor.
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Key Takeaway Points and Lessons Learned from QCon San Francisco 2017
The eleventh annual QCon San Francisco was the biggest yet, bringing together over 1,800 team leads, architects, project managers, and engineering directors.
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InfoQ Call for Articles
InfoQ provides software engineers with the opportunity to share experiences gained using innovator and early adopter stage techniques and technologies with the wider industry. We are always on the lookout for quality articles and we encourage practitioners and domain experts to submit feature-length (2,000 to 3,000 word) papers that are timely, educational and practical.