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AI, ML & Data Engineering

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.

InfoQ
on Jul 31, 2018
AI, ML & Data Engineering

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.

Srini Penchikala
on Feb 23, 2018
Architecture & Design

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.

InfoQ
on Jan 07, 2018
AI, ML & Data Engineering

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.

InfoQ
on Apr 19, 2017
AI, ML & Data Engineering

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.

InfoQ
on Nov 21, 2016
AI, ML & Data Engineering

InfoQ eMag: Graph Databases

This eMag focuses on the graph database landscape and the real world use cases of graph databases. It includes articles and interviews covering topics like data modeling in graph databases and how companies use graph databases in their application. It also includes an article on full stack web development using a graph database.

InfoQ
on Oct 27, 2015
InfoQ eMag: Hadoop

Apache Hadoop is proving useful in deriving insights out of large amounts of data, and is seeing rapid improvements. Hadoop 2 now goes beyond Map-Reduce; it is more modular, pluggable and flexible and it fits a variety of use cases better. We explore this as well as some tools that can help utilize Hadoop better.

InfoQ
on May 19, 2014
InfoQ eMag: The Best of NoSQL

The InfoQ NoSQL eMag brings together a selection of popular NoSQL articles recently published on InfoQ.com. Get a complete overview of the current NoSQL movement, learn how NoSQL relates to the CAP Theorem, and get practical guidance on setting up and using a popular NoSQL database.

InfoQ.com
on Jun 03, 2013
Good Relationships

With Spring Data, the ever popular Spring Framework has cultivated a new patch of ground, bringing Big Data and NOSQL technology like Neo4j to enterprise developers. This guide introduces you to Spring Data Neo4j, using the fast, powerful and scalable graph database Neo4j to enjoy the benefits of having good relationships in your data.

Michael Hunger
on Jan 30, 2012