[La Tribune] BigDataFr recommande : La France se prépare au futur de son industrie

BigDataFr recommande : La France se prépare au futur de son industrie […] Robots et capteurs, simulation et connectivité, intégration de la culture digitale et bouleversement des modèles économiques, l’industrie se transforme en profondeur. Cette mutation est organisationnelle autant que technologique. Toutes les entreprises françaises n’ont pas encore pris conscience des changements profonds qui nécessitent […]

[arXiv] BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency

BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency […] We present a roadmap to guide European research efforts towards a socially responsible big data economy that maximizes the positive impact of big data in environment and energy efficiency. The goal of the roadmap is to […]

[HAL] BigDataFr recommends: Stream-based Reasoning for IoT Applications – Proposal of Architecture and Analysis of Challenges

BigDataFr recommends: Stream-based Reasoning for IoT Applications – Proposal of Architecture and Analysis of Challenges Abstract […] As distributed IoT applications become larger and more complex, the pure processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pieces of information must be combined […]

[La Tribune] BigDataFr recommande : Data marketing : la startup Mediarithmics lève 3 millions d’euros pour s’internationaliser

BigDataFr recommande : Data marketing : la startup Mediarithmics lève 3 millions d’euros pour s’internationaliser […] Pas facile de se faire un nom dans un secteur, le marketing personnalisé, dominé par des géants américains tels que SAP, Oracle, IBM ou encore HP. Pourtant, la startup française Mediarithmics a décidé de se lancer dans le bain. […]

[Dataconomy] BigDataFr recommends: Trends Shaping Machine Learning in 2017

BigDataFr recommends: Trends Shaping Machine Learning in 2017 […] Technologies in the field of data science are progressing at an exponential rate. The introduction of Machine Learning has revolutionized the world of data science by enabling computers to classify and comprehend large data sets. Another important innovation which has changed the paradigm of the world […]

[Datasciencecentral] BigDataFr recommends: Reinforcement Learning and AI

BigDataFr recommends: Reinforcement Learning and AI […] If you poled a group of data scientist just a few years back about how many machine learning problem types there are you would almost certainly have gotten a binary response: problem types were clearly divided into supervised and unsupervised. Supervised: You’ve got labeled data (clearly defined examples). […]

[arXiv] BigDataFr recommends: Massively-Parallel Feature Selection for Big Data

BigDataFr recommends: Massively-Parallel Feature Selection for Big Data […] We present the Parallel, Forward-Backward with Pruning (PFBP) algorithm for feature selection (FS) in Big Data settings (high dimensionality and/or sample size). To tackle the challenges of Big Data FS PFBP partitions the data matrix both in terms of rows (samples, training examples) as well as […]

[The Conversation] BigDataFr recommande : Des patients indispensables aux « living labs », ces plates-formes d’innovation ouverte

BigDataFr recommande : Des patients indispensables aux « living labs », ces plates-formes d’innovation ouverte […] Et si l’innovation en santé se faisait non seulement pour les patients mais… avec les patients ? Traditionnellement, ce sont les professionnels de santé qui partent en quête de nouvelles solutions. Ils mènent des travaux de recherche fondamentale et […]