BigDataFr recommends: Mathematics in Data Science – (July 28-30, 2015) – ICERM – Topical Workshops Topic: BigData Visual Analysis – Chris Johnson – University of Utah Brian Laball, Isani Cayetano Source: https://icerm.brown.edu/
Devenir DataScientist
[France Info] BigDataFr recommande : Quand les algorithmes prédiront l’avenir
BigDataFr recommends: Quand les algorithmes prédiront l’avenir Ecouter l’émission L’informatique peut-elle prédire l’avenir ? De plus en plus d’algorithmes servent à anticiper les événements de la vie quotidienne : dans les transports, la sécurité ou encore l’économie et la santé… Rappelez-vous le film Minority Report, que l’on cite toujours en exemple. Grâce à des sortes […]
[analyticsvidhya] BigDataFr recommends: Quick Guide to learn Statistics for R Users-with Titanic Data Set #datascientist
BigDataFr recommends: Quick Guide to learn Statistics for R Users-with Titanic Data Set People are keen to pursue their career as a data scientist. And why shouldn’t they be? After all, this comes with a pride of holding the sexiest job of this century. But, in order to become one, you must master ‘statistics’ in […]
[HAL] BigDataFr recommends: Towards Cloud big data services for intelligent transport systems
BigDataFr recommends: Towards Cloud big data services for intelligent transport systems Abstract In later years, the increase in computation power and data storage has opened new perspectives to data analysis. The possibility to analyse big data brings new insights into obscure and useful correlations in data providing undiscovered knowledge. Applying big data analytics to the […]
[arXiv] BigDataFr recommends: An Extended classification and Comparison of NoSQL Big Data Models
BigDataFr recommends: An Extended classification and Comparison of NoSQL Big Data Models In last few years, the volume of the data has grown manyfold. The data storages have been inundated by various disparate potential data outlets, leading by social media such as Facebook, Twitter, etc. The existing data models are largely unable to illuminate the […]
[HAL] BigDataFr recommends: Data-intensive HPC-opportunities and challenges #datascientist
BigDataFr recommends: Data-intensive HPC-opportunities and challenges Abstract Data-intensive computing and HPC are two different computing paradigms (data-centric versus compute-centric), targeting different application domains (mainly business data processing versus computational science). But with the advent of big data, the blending of these areas into data-intensive HPC offers new opportunities to solve bigger problems, as well as […]
[O’R] BigDataFr recommends: Five principles for applying data science for social good #datascientist
BigDataFr recommends: Five principles for applying data science for social good Editor’s note: Jake Porway expanded on the ideas outlined in this piece in his Strata + Hadooop World NYC 2015 keynote address, « What does it take to apply data science for social good? » “We’re making the world a better place.” That line echoes from […]
[O’R] BigDataFr recommends: Accelerating real-time analytics with Spark
BigDataFr recommends: Accelerating real-time analytics with Spark Integration of the data supply chain is key to a reliable and fast big data analytics deployment. Apache Hadoop is a mature development framework, which coupled with its large ecosystem, and support and contributions from key players such as Cloudera, Hortonworks, and Yahoo, provides organizations with many tools […]
[ISPRS] BigDataFr recommends: QOS Management in Real-Time Spatial Using Big data Feedback Control Scheduling #datascientist
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-3/W5, 2015 ISPRS Geospatial Week 2015, 28 Sep – 03 Oct 2015, La Grande Motte, France BigDataFr recommends: QOS Management in Real-Time Spatial Using Big data Feedback Control Scheduling Commission II, WG II/4 Key words: Geographic Information System, Real-Time Spatial Big Data, Heterogeneous […]
[MIT] BigDataFr recommends: Big Data Privacy Scenario – Big Data Privacy Working Group Chairs
BigDataFr recommends: Big Data Privacy Scenario – Big Data Privacy Working Group Chairs Executive Summary (Excerpt) Karen Sollins (MIT) The MIT BigData Privacy Working Group launched a series of workshops beginning in 2013 to explore the challenges and possible technological solutions to elements of those challenges. As a success or to those workshops, the Working […]