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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.
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Improve Your Node.js App Throughput One Micro-optimization at a Time
To improve the performance of a Node.js application that involves IO, you need to understand how your CPU cycles are spent and what is preventing higher degrees of parallelism in your application. In this article, Jorge Bay shares his insights on areas that cause throughput degradation and tips on how to boost performance.
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Creating an HTML UI for Desktop .NET Applications
Developers are looking for ways to employ the richness of the Web UI in desktop applications. The common approach is to embed a browser component to render the HTML UI within the desktop app.
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Refactoring to Reactive - Anatomy of a JDBC migration
Reactive programming offers built-in solutions for some of the most difficult challenges in programming, including concurrency management and flow control. So you might ask - how do I get there; can I introduce it in phases? In this article we transform a legacy application to a reactive model using RxJava.
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Polymorphism of MVC-esque Web Architecture: Real Time Reactive Fulfillment
The reactive ideal of the MVC architectural approach was diminished in web applications during the first two decades of the web age. Recent advancements have revitalized the reactive idea of the MVC architecture. In this article, Brent Chen and Victor Chen show how developers can leverage the dWMVC and pWMVC architectural paradigms to create real time reactive application behaviors.
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Swift and Objective-C Runtime Programming
Since a few months ago, a debate has been going on within the Objective-C/Swift developer community concerning the lack of dynamic features in Swift and the importance that runtime programming plays in Objective-C and Cocoa. InfoQ has spoken with Swift developers Chris Eidhof and Drew Crawford to learn more about these potential issues.
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Key Takeaway Points and Lessons Learned from QCon San Francisco 2016
The 10th annual QCon San Francisco was the biggest yet, bringing together over 1500 team leads, architects, project managers, and engineering directors. Over 125 practitioner-speakers presented 92 full-length technical sessions and 32 in-depth tutorials, providing deep insights into real-world architectures and state of the art software development practices from a practitioner’s perspective.
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Mobile Development Efficiency with NativeScript and Angular
To meet both consumer demand and expectations, companies must develop for both mobile and web. Developing for both platforms is complex, but with the right tools and framework, the process is a little easier. In this article, TJ VanToll shows how to use NativeScript and Angular to develop cross platform apps.
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Book Review: Learn Apache JMeter by Example
JMeter is an indispensable tool for testing load and functionality of multi-tiered applications comprised of web front ends, JVM servers and a wealth of NoSQL and relational databases. This book is the manual that should have been included to help surmount the learning curve.
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Article Series: Getting a Handle on Data Science as a Software Developer
Software developers and managers are realizing that they need data science among their skills, to be able to tackle pressing problems. In this series, field experts provide guidance to help us navigate among the available data analysis options. They explore ways of understanding where data science is needed and where it’s not, and how to turn it into an asset.
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Data Science up and down the Ladder of Abstraction
Although Clojure lacks the extensive toolbox and analytic community of the most popular data science languages, R and Python, it provides a powerful environment for developing statistical thinking and for practicing effective data science.