BigDataFr recommends: Train faster, generalize better – Stability of stochastic gradient descent ‘We show that any model trained by a stochastic gradient method with few iterations has vanishing generalization error. We prove this by showing the method is algorithmically stable in the sense of Bousquet and Elisseeff. Our analysis only employs elementary tools from convex […]
Documentation
[HAL] BigDataFr recommends: Random forests and big data #datascientist
BigDataFr recommends: A Prime Number Based Approach for Closed Frequent Itemset Mining in Big Data Abstract Big Data is one of the major challenges of statistical science and has numerous consequences from algorithmic and theoretical viewpoints. Big Data always involves massive data but it also often includes data streams and data heterogeneity. Recently some statistical […]
[O’R] BigDataFr recommends: Evaluating Machine Learning Models -Free Report #machinelearning
BigDataFr recommends: Evaluating Machine Learning Models -Free Report Description Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. Now you have help. With […]
[informatiquenews] BigDataFr recommande : L’étincelle Spark embrase le big data
BigDataFr recommande : L’étincelle Spark embrase le big data « Cloudera veut pousser Spark plus près d’Hadoop en remplacement de MapReduce. Avec le rachat d’Onyara, Hortonworks veut unifier la plate-forme Hadoop. Dans l’univers Hadoop, Hortonworks, Cloudera et MapR sont les trois étoiles les plus brillantes avec des positionnements différents : pure open source pour le premier, […]
[McKinsey] BigDataFr recommends: ‘Transformer in chief’ -The new chief digital officer #CDO #CTO
BigDataFr recommends: ‘Transformer in chief’ -The new chief digital officer ‘In the alphabet soup that is today’s crowded C-suite, few roles attract as much attention as that of the chief digital officer, or CDO. While the position isn’t exactly new, what’s required of the average CDO is. Gone are the days of being responsible for […]
[CIO] BigDataFr recommends: How data analytics helps managers be more effectiv
BigDataFr recommends: How data analytics helps managers be more effective ‘Big data analysis is helping organizations better analyze their customers, predict the competitive landscape and suss out emerging trends before they go mainstream — all of which helps companies maintain a competitive edge. But turn the lens inward, and big data can also be a […]
[Convention Big Data – Université Paris Saclay] BigDataFr recommande : Big Data Business Convention – 24 & 25 Novembre 2015 à HEC Paris – Inscription Gratuite !
Inscription gratuite BigDataFr recommande : Big Data Business Convention – 24 & 25 Novembre 2015 à HEC Paris Sous la haute-autorité d’Axelle Lemaire, secrétaire d’état chargé du numérique Keynote « Machine Learning »: Christopher Bishop, directeur Microsoft Research Cambridge Inscrivez-vous ! L’Université Paris-Saclay organise une Convention d’Affaires sur la thématique « Big Data » à Saclay. Il […]
[Cloudera] BigDataFr recommends: Ibis on Impala – Python at Scale for Data Science
BigDataFr recommends: Ibis on Impala – Python at Scale for Data Science ‘This new Cloudera Labs project promises to deliver the great Python user experience and ecosystem at Hadoop scale. Across the user community, you will find general agreement that the Apache Hadoop stack has progressed dramatically in just the past few years. For example, […]
[Githubs] BigDataFr recommends: Exploratory Data Analysis
BigDataFr recommends: Exploratory Data Analysis ‘Here we are again, with a new episode in our series about doing data science with the two most popular open-source platforms you can use for the job nowadays. In this case we will have a look at a crucial step of the data analytics process, that of the Exploratory […]
[HAL] BigDataFr recommends: Compression-based nonnegative tensor CP decomposition of hyperspectral big data
BigDataFr recommends: Compression-based nonnegative tensor CP decomposition of hyperspectral big data […]’New hyperspectral missions will collect huge amounts of hyperspectral data. Besides, it is possible now to acquire time series and multiangular hyperspectral images. The process and analysis of these big data collections will require common hyperspectral techniques to be adapted or reformulated. The tensor decomposition, […]