InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Testing RxJava2
You are ready to explore reactive opportunities in your code but you are wondering how to test out the reactive idiom in your codebase. In this article Java Champion Andres Almiray provides techniques and tools for testing RxJava2.
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Article Series: An Introduction to Machine Learning for Software Developers
Get an introduction to some powerful but generally applicable techniques in machine learning for software developers. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.
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Book Review: Andrew McAfee and Erik Brynjolfsson's "The Second Machine Age"
Andrew McAffee and Erik Brynjolfsson begin their book The Second Machine Age with a simple question: what innovation has had the greatest impact on human history?
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Deterministic Execution on the JVM
For many use cases (for example cryptocurrency ledgers), we need to ensure that any action will execute deterministically and terminate. In this article, Ben Evans reviews the theory behind the WhitelistClassLoader.
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Learning Paths: QCon London Expert Recommendations
Advice on the best talks to attend at QCon London 2017 from London Thought Leaders.
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Real-World, Man-Machine Algorithms
In this article, we'll talk about the end-to-end flow of developing machine learning models: where you get training data, how you pick the ML algorithm, what you must address after your model is deployed, and so forth.
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RXJava2 by Example
In the ongoing evolution of paradigms for simplifying concurrency under load, the most promising addition is reactive programming, a specification that provides tools for handling asynchronous streams of data and for managing flow-control, making it easier to reason about overall program design. In this article we overcome the learning curve with a gentle progression of examples.
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Anomaly Detection for Time Series Data with Deep Learning
This article introduces neural networks, including brief descriptions of feed-forward neural networks and recurrent neural networks, and describes how to build a recurrent neural network that detects anomalies in time series data. To make our discussion concrete, we’ll show how to build a neural network using Deeplearning4j, a popular open-source deep-learning library for the JVM.
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Q&A with Immuta on the Implications of EU’s General Data Protection Regulation (GDPR)
InfoQ talked with Immuta’s Andrew Burt and Steve Touw, to better understand the implications and challenges of the EU's Global Data Protection Regulation, which will come into effect in May 2018.
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Practicing Machine Learning with Optimism
Using machine learning to solve real-world problems often presents challenges that weren't initially considered during the development of the machine learning method. This article addresses a few examples of such issues and hopefully provides some suggestions (and inspiration) for how to overcome the challenges using straightforward analyses on the data you already have.
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Introduction to Machine Learning with Python
This series will explore various topics and techniques in machine learning, arguably the most talked-about area of technology and computer science over the past several years. We’ll begin, in this article, with an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?
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Building Reactive Applications with Akka Actors and Java 8
Akka and Java 8 make it possible to create distributed microservice-based systems that just a few years ago were the stuff of dreams. Actor based systems enable developers to create quickly evolving microservice architectures that can elastically scale systems to support huge volumes of data.