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AI, ML & Data Engineering

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.

Alyssa Frazee
on Feb 02, 2017
AI, ML & Data Engineering

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?

Michael Manapat
on Jan 28, 2017
Java

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.

Markus Eisele
on Jan 23, 2017
AI, ML & Data Engineering

An Introduction to Differential Privacy

Differential privacy leapt from research papers to tech news headlines last year when, in the WWDC keynote, Apple VP of Engineering Craig Federighi announced Apple’s use of the concept to protect user privacy in iOS. This article gives a definition of differential privacy and example of differentially private algorithms.

Charlie Cabot
on Jan 22, 2017
AI, ML & Data Engineering

Analysis and Mitigation of NoSQL Injections

NoSQL data storage systems lack the security measures and awareness that are required for data protection. Because code analysis alone is insufficient to prevent attacks in today's typical large-scale deployment, certain mitigations should be done throughout the entire software life cycle.

Alexandra-Shulman-Peleg Anton Puzanov Aviv Ron
on Jan 18, 2017
AI, ML & Data Engineering

Cassandra: The Definitive Guide, 2nd Edition Book Review and Interview

Cassandra: The Definitive Guide, 2nd Edition book authored by Jeff Carpenter and Eben Hewitt covers the Cassandra NoSQL database version 3.0. Authors discuss several different important topics related to this popular database, including data modeling and Cassandra architecture. InfoQ spoke with Jeff Carpenter about the book and Cassandra database current features and future roadmap.

Srini Penchikala
on Jan 05, 2017
Java

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.

Nicolae Marasoiu
on Dec 22, 2016
Architecture & Design

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.

Abel Avram
on Dec 14, 2016
AI, ML & Data Engineering

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.

Francine Bennett
on Dec 05, 2016
AI, ML & Data Engineering

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.

Henry Garner
on Dec 02, 2016
Java

Reactor by Example

Reactor, like RxJava 2, is a fourth generation reactive library launched by Spring custodian Pivotal. It builds on the Reactive Streams specification, Java 8, and the ReactiveX vocabulary. In this article, we’ll draw a parallel between Reactor and RxJava, and showcase the common elements as well as the differences.

Simon Baslé
on Nov 29, 2016
AI, ML & Data Engineering

Getting Started with Machine Learning

A quick introduction to the machine learning field, exploring both supervised and unsupervised approaches.

Rafael Fernandes
on Nov 19, 2016

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