Machine Learning

This article is a companion to Creative Production Flows for Distributed Innovation Teams. It should be noted that the Innovation Accelerator is now part of SogetiLabs’ Thinkubator Business enterprise innovation platform and services.

What happens when you ask a group of technology specialists about “What will be the latest tech company on the stock exchange in 10 years’ time?”

Machine learning is getting more traction. The willingness of companies to use ML models in production for their daily business is growing.

Crowdsourcing Label Aggregation: Labelled datasets are crucial for training machine learning research, both in academia and in industry.

Zooming in on the potential applications of quantum computing in predicting the evolution of COVID-19 using quantum machine learning.

Take a look at our most read and shared blog posts from September 2020.

There is a constant ask from the customer on how to optimize the overall QA (Quality assurance) activities in terms of reducing cycle time, improving quality by reducing production defects, focused testing to get maximum defects in early development phases.

With the increasing use of ML and AI, how can retailers boost efficiency and productivity while actively engaging with consumers?

Applying machine learning algorithms to your business process can be quite beneficial: whether it is to predict incoming workloads to better allocate internal and external resources, or to segment customer groups to personalize marketing campaigns, machine learning is the key to success.

A brief overview of Natural Computing with some hints as to how some of the research can be used today to enhance the way we build computer-based systems.

What are Cloudlets, what are it's benefits and why we need Cloudlets?

In this article, I will show how to use ML.Net (Machine Learning framework for .Net developers) to create an API service that will analyze comments sentiments (e.g. positive or negative sentiment of the comment).