[HAL] BigDataFr recommends: Implications of big data for knowledge organization

BigDataFr recommends: Implications of big data for knowledge organization Abstract […] In this paper, we propose a high-level analysis of the implications of Big Data for Knowledge Organisation (KO) and Knowledge Organisation Systems (KOSs). We confront the current debates within the KO community about the relevance of universal bibliographic classifications and the thesaurus in the […]

[Usine Digitale] BigDataFr recommande : L’IoT, nouvelle locomotive de la SNCF

BigDataFr recommande : L’IoT, nouvelle locomotive de la SNCF […] La SNCF jette son dévolu sur l’Internet des objets. « Dans notre entreprise, c’est l’IoT qui devient le principal levier de performance et d’efficacité. La vraie révolution technologique c’est l’IoT », a lancé jeudi 18 mai 2017, Guillaume Pepy, le président du groupe de transport, lors d’une […]

[ZDNet] BigDataFr recommande : Transformer le big data en perspectives utiles en 2017

BigDataFr recommande : Transformer le big data en perspectives utiles en 2017 […] Selon les estimations de Constellation Research, au moins 60 % des données que les entreprises considèrent comme cruciales demeureront en dehors de l’entreprise d’ici 2020. Comment donc le cloud peut-il aider les DSI à exploiter au mieux les informations que leur entreprise […]

[ArXiv] BigDataFr recommends: Data Visualization on Day One: Bringing Big Ideas into Intro Stats Early and Often

BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics […] In a world awash with data, the ability to think and compute with data has become an important skill for students in many fields. For that reason, inclusion of some level of statistical computing in many introductory-level courses has grown more common […]

[Analyticsvidhya] BigDataFr recommends: Understanding and coding Neural Networks From Scratch in Python and R

BigDataFr recommends: Understanding and coding Neural Networks From Scratch in Python and R Introduction […] You can learn and practice a concept in two ways: Option 1: You can learn the entire theory on a particular subject and then look for ways to apply those concepts. So, you read up how an entire algorithm works, […]