[arXiv] BigDataFr recommends: Bayesian Nonlinear Support Vector Machines for Big Data

BigDataFr recommends: Bayesian Nonlinear Support Vector Machines for Big Data […] We propose a fast inference method for Bayesian nonlinear support vector machines that leverages stochastic variational inference and inducing points. Our experiments show that the proposed method is faster than competing Bayesian approaches and scales easily to millions of data points. It provides additional […]

[Dataconomy] BigDataFr recommends: High Performance Big Data Analysis Using NumPy, Numba & Python Asynchronous Programming

BigDataFr recommends: High Performance Big Data Analysis Using NumPy, Numba & Python Asynchronous Programming […] At that time, based on this question, my first simple answer was the Python List object. I used the List object in many Data Science projects including Data Pipeline and Extract-Transform-Load (ETL) production system. Then the following questions came to […]

[La Tribune] BigDataFr recommande : Des algorithmes et des hommes : quel avenir pour le recrutement ?

BigDataFr recommande : Des algorithmes et des hommes : quel avenir pour le recrutement ? […] Le bruit court, la rumeur enfle : Facebook et Linkedin seraient sur le point d’uberiser le marché du recrutement. Le spectre d’une automatisation galopante se lève et bouscule ses acteurs traditionnels. Stupeur et tremblements… Mais « toute théorie s’expose […]

[Datasciencecentral] BigDataFr recommends: Better Banking with help of Analytics and Machine learning

BigDataFr recommends: Better Banking with help of Analytics and Machine learning […] In 2015, I was working at Diebold where we build ATM machine hardware and software and complete ecosystem around the ATM. When we talk about ATM machine, it is a collection of very complex small hardware which collectively performs tasks. And typically, when […]

[HAL] BigDataFr recommends: Developing a Smart Service System to Enrich Bike Riders’ Experience

BigDataFr recommends: Developing a Smart Service System to Enrich Bike Riders’ Experience Abstract […] Social sensing via mobile apps complements physical sensing (e.g., IoT) by substantially extending the horizon we know about our daily life in real time. This paper discusses how we can integrate physical and social sensing to enable better and smarter services, […]

[Dataconomy] BigDataFr recommends: Three signs you might be experiencing a NoSQL hangover

BigDataFr recommends: Three signs you might be experiencing a NoSQL hangover […] Selecting a database technology to build your new application on is often a complex and even stressful process. While the business use case for the application is pretty straightforward, the nuances of the data platform that will power it are often much less […]

[arXiv] BigDataFr recommends: Big Data vs. complex physical models: a scalable inference algorithm

BigDataFr recommends: Big Data vs. complex physical models: a scalable inference algorithm […] The data torrent unleashed by current and upcoming instruments requires scalable analysis methods. Machine Learning approaches scale well. However, separating the instrument measurement from the physical effects of interest, dealing with variable errors, and deriving parameter uncertainties is usually an after-thought. Classic […]

[La Tribune] BigDataFr recommande : Agriculture digitale : comment Atos et TerraNIS tirent ensemble profit des satellites

BigDataFr recommande : Agriculture digitale : comment Atos et TerraNIS tirent ensemble profit des satellites […] Le potentiel du big data issu de l’observation de la Terre par les satellites Sentinel, fourni en open source par l’Agence spatiale européenne, attire les grands des services numériques vers des terrains inexplorés. Jusqu’à l’agriculture, où l’arrivée du digital […]