The idea of model fusions is pretty simple. You combine the predictions of a bunch of separate classifiers into a single, uber-classifier prediction, in theory, better than the predictions of its individual constituents.

As my colleague Teresa Álverez mentioned in a previous post, however, this doesn’t typically lead to big gains in performance. We’re typically talking 5-10% improvements even in the best case. In many cases, OptiML will find something as good or better than any combination you could try by hand.


Source de l’article sur DZONE (AI)

“Digital twins” are commonly associated with Industrial Internet of Things installations, in which they are widely used. They generally work as follows: the sensors from a machine are mapped to a digital abstraction, or “twin,” making it easier to monitor the machine and know when it needs maintenance. The digital twin can also be used to model the lifecycle of the machine, predicting when, for example, individual parts are likely to fail. In fact, any physical asset that is receptive to monitoring and prediction, such as a city or even the human body, could benefit from a digital twin.

But the “digital twin” as a concept can also be extended in a different direction—to non-physical modeling. One particular area where it can be effective is in managing customer relationships, i.e. tracking and accurately predicting a customer’s needs. Basically, it can enable businesses to offer “the right product at the right time.”

Source de l’article sur DZone (Agile)

“We think we listen, but very rarely do we listen with real understanding, true empathy. Yet listening, of this very special kind, is one of the most potent forces for change that I know.” – Carl Rogers

This thought came to my mind when we were doing the design thinking workshop. We were emphasizing the empathy aspect with the people who will build a product and consume the solutions. Why do we not, as coaches, practice the same our coaching teams? That’s how I started digging more into this.

A few of my fellow coaches are sharing stories from their team, speak about how Scrum Masters will not allow others to talk. He/she will keep talking about what Scrum guides say and what we should do according to them. He/she as a Scrum Master will not listen to the team members.

Source de l’article sur DZONE

Part 3: Claims Management

An insurance claim is "a formal request to an insurance company for coverage or compensation for a covered loss or policy event" (source: www.investopedia.com). Once initiated, the claim often goes through a complex process with one of two possible outcomes — the claim is either accepted, leading to a settlement, or rejected. The claims process would typically be: contact the insurance company, start of the claimant investigation, check the policy coverage, evaluate the damage and arrange compensation payment.


Source de l’article sur DZONE (AI)

In an ideal world, every project is finished on time, and within the estimated budget. Even better, the budget has allowed teams to develop additional features and test everything one more time before the release. In the real world, the development process can encounter several difficulties, and technical debt is among the most common issues the project may face. It is essential to understand what technical debt is, how to evaluate it and especially how to tackle it.

What Is Technical Debt?

Technical debt is the additional work needed to complete the software development. But this notion does not refer solely to the projects that are in development. This issue often follows the projects that have been production for some time. This may be anything, like some module written on legacy technology, that holds the project back from including a new functionality or influence overall software stability. In this particular case, technical debt can be calculated as the time or money needed for the refactoring of this module’s code or porting it to the new technology. But usually it is never that simple and the software system includes a number of drawbacks that can be included in the technical debt of the project.

Source de l’article sur DZone (Agile)

Introduction

Java developers usually deal with collections such as ArrayList and HashSet. Java 8 came with lambda and the streaming API that helps us to easily work with collections. In most cases, we work with a few thousands of items and performance isn’t a concern. But, in some extreme situations, when we have to travel over a few millions of items several times, performance will become a pain.

I use JMH for checking the running time of each code snippet.

Source de l’article sur DZONE

PwC et BAE Systems mettent le doigt sur une opération d’espionnage fondée sur des attaques contre les prestataires de gestion informatique externalisée.
Source de l’article sur ITEXPRESSO

Entre Orange, SFR et Bouygues Telecom, les annonces se suivent et se ressemblent parfois. Les trois opérateurs ont choisi la date du 3 juillet 2018 pour communiquer sur leurs expérimentations respectives dans les réseaux 5G. Du côté de Bouygues Telecom, on a officiellement ouvert un « premier pilote » en France.

Source : 5G : la France passe vraiment en phase pilote

Votre nombre d’abonnés risque peut-être de diminuer bientôt sur Twitter. Il est possible que ces comptes n’aient pas cessés de vous suivre, mais qu’ils soient plutôt visés par une nouvelle mesure du réseau social. [Lire la suite]

Source : Pourquoi vous allez perdre des abonnés sur Twitter

Dans la famille conteneurisation, on demande Jib. Google élargit la communication sur cette bibliothèque open source destinée à la création d’images Docker et OCI à partir d’applications Java. L’initiative coïncide avec le passage en version 0.9.3 des modules qui permettent d’intégrer Jib dans les moteurs de production Maven et Gradle*.

Source : Applications Java et conteneurs Docker : Google fait la jonction via Jib