InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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The InfoQ eMag - Modern Data Engineering: Pipeline, APIs, and Storage
In this second edition of the Modern Data Engineering eMag, we’ll explore the ways in which data engineering has changed in the last few years. Data engineering has now become key to the success of products and companies. And new requirements breed new solutions.
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InfoQ eMag: Modern Data Engineering
Data engineers and software architects will benefit from the guidance of the experts in this eMag as they discuss various aspects of breaking down traditional silos that defined where data lived, how data systems were built and managed, and how data flows in and out of the system.
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The InfoQ eMag - The InfoQ Software Trends Report 2019: Volume 1
This eMag brings together the complete set of reports from the last 12 months and as such represents various points in time. We hope that this format provides InfoQ readers, from developers to CTOs, with a concise summary of the professional software landscape. We encourage you to explore these technologies for yourselves
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The InfoQ eMag: QCon 2018 Retrospective
We take a look back at best QCon highlights in 2018, including QCon London, QCon.AI, QCon New York and QCon San Francisco.
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The InfoQ eMag: Tech Ethics
In an ideal world, devs would like to be ethical in their work but they ultimately don’t consider it to be part of their responsibilities. This eMag sets out to understand why they might feel that way and whose job it is to take reasonable steps to ensure that tech products don’t harm users or anyone else.
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The Morning Paper Issue 8 - AI Edition
Welcome to this AI-themed edition of The Morning Paper Quarterly. We've selected five paper write-ups which first appeared on The Morning Paper blog over the last year.
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The InfoQ eMag: Real-World Machine Learning: Case Studies, Techniques and Risks
Machine learning (ML) and deep-learning technologies like Apache Spark, Flink, Microsoft CNTK, TensorFlow, and Caffe brought data analytics to the developer community. This eMag focuses on the current landscape of ML technologies and presents several associated real-world case studies.
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Big Data Processing with Apache Spark
In this mini-book, the reader will learn about the Apache Spark framework and will develop Spark programs for use cases in big-data analysis. The book covers all the libraries that are part of Spark ecosystem, which includes Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and Spark GraphX.
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The InfoQ eMag: Streaming Architecture
This InfoQ emag aims to introduce you to core stream processing concepts like the log, the dataflow model, and implementing fault-tolerant streaming systems.
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The InfoQ eMag: Introduction to Machine Learning
InfoQ has curated a series of articles for this introduction to machine learning eMagazine, covering everything from the very basics of machine learning (what are typical classifiers and how do you measure their performance?) and production considerations (how do you deal with changing patterns in data after you’ve deployed your model?), to newer techniques in deep learning.
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The InfoQ eMag: Getting a Handle on Data Science
This eMag looks at data science from the ground up, across technology selection, assembling raw and unstructured data, statistical thinking, machine learning basics, and the ethics of applying these new weapons.
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The InfoQ eMag: The Current State of NoSQL Databases
This eMag focuses on the current state of NoSQL databases. It includes articles, a presentation and a virtual panel discussion covering a variety of topics ranging from highly distributed computations, time series databases to what it takes to transition to a NoSQL database solution.
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