BigDataFr recommends: Apache Spark:Powering applications on-premise and in the cloud The O’Reilly Data Show Podcast: Patrick Wendell on the state of the Spark ecosystem. ‘As organizations shift their focus toward building analytic applications, many are relying on components from the Apache Spark ecosystem. I began pointing this out in advance of the first Spark Summit […]
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[Le Figaro Etudiant] Big Data : quels sont les meilleurs programmes pour se spécialiser #datascientist
BigDataFr recommande : Big Data : quels sont les meilleurs programmes pour se spécialiser? ‘«Big Data», depuis quelques mois, le concept est partout. Le comité de pilotage de la nouvelle France industrielle a ainsi validé il y a presque un an le «plan Big Data», qui devrait permettre de créer 130 000 emplois en France […]
[rayli] BigDataFr recommends: Top 10 data mining algorithms in plain English #datascientist
BigDataFr recommends: Top 10 data mining algorithms in plain English ‘Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this survey paper. Once you know what they are, how they work, what they do and where you can find them, […]
[O’R] BigDataFr recommends: Validating data models with Kafka-based pipelines #datascientist #machinelearning #kafka #hadoop #cloudera
BigDataFr recommends: Validating data models with Kafka-based pipelines ‘A/B testing is a popular method of using business intelligence data to assess possible changes to websites. In the past, when a business wanted to update its website in an attempt to drive more sales, decisions on the specific changes to make were driven by guesses; intuition; […]
[O’R] BigDataFr recommends: BigDataFr recommends: Designers as data scientists #datascientist
BigDataFr recommends: Designers as data scientists ‘It might feel like using data is big news now, but the truth is that we’ve been using data for a long time. For the past 20 years, we’ve been moving and replicating more and more experiences that we used to have in the physical world into the digital […]
[arXiv] BigDataFr recommends: Identifying Dwarfs Workloads in Big Data Analytics #datascientist #machinelearning
BigDataFr recommends: Identifying Dwarfs Workloads in Big Data Analytics ‘Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data computing impose big challenges on big data benchmarking. How can we construct a benchmark suite using a minimum set of units […]
[Datascience – CDiscount] BigDataFr recommande : Challenge Big Data – Catégorisation de produits pour le e-commerce #datascientist #ecommerce #challenge
BigDataFr recommande : Challenge Big Data – Catégorisation de produits pour le e-commerce Date limite de participation : 16 août 2015 – 15.000 € à gagner Description du Challenge Leader de la vente en ligne en France, Cdiscount a conquis les clients français avec ses offres innovantes et variées et ses prix les moins […]
[arXiv] BigDataFr recommends: Online Updating of Statistical Inference in the Big Data Setting
BigDataFr recommends: Online Updating of Statistical Inference in the Big Data Setting ‘We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models […]
[J-4 – A ne pas manquer !] BigDataFr recommande : Présentation du Label Big Data de l’UPMC – 29 mai 2015 #datascientist
présente Les Formations supérieures Big Data Incontournables: Venez les rencontrer ! J-4 : Présentation du Label Big Data de l’UPMC – 29 mai 2015, 14h Lieu : Université Pierre et Marie Curie (UPMC), Paris 5e L’accès au Label Big Data de l’UPMC nécessite impérativement l’inscription à l’une des 5 filières du Master de Mathématiques et […]
[ERIC – Institut of Education Sciences] BigDataFr recommends: Research on Implementing Big Data Technology, People, & Processes #datascientist #machinelearning
BigDataFr recommends: Research on Implementing Big Data: Technology, People, & Processes ‘Abstract: When many people hear the term “big data”, they primarily think of a technology tool for the collection and reporting of data of high variety, volume, and velocity. However, the complexity of big data is not only the technology, but the supporting processes, […]