[Datasciencecentral] BigDataFr recommends: Data Scientists – Are You Prepared For Your Next Interview?

BigDataFr recommends: Data Scientists – Are You Prepared For Your Next Interview? […] You’ve perfected your CV, got great experience under your belt, maybe a PhD and can wrangle data amongst the finest but just how prepared are you for your next interview? Just the thought of the face-to-face interview stage is enough to strike […]

[La Tribune] BigDataFr recommande : De l’importance des mathématiques dans les traitements de données

BigDataFr recommande : De l’importance des mathématiques dans les traitements de données […] Typiquement, les données issues des réseaux sociaux, de Facebook, Twitter ou Instagram sont principalement textuelles et donc nécessitent d’importants travaux pour les exploiter. Ceux qui ont une formation en mathématique, ou mieux encore en statistiques ont l’habitude de penser des données comme […]

[Dataconomy] BigDataFr recommends: FinTech in the Banking Environment

BigDataFr recommends: FinTech in the Banking Environment […] Who goes there, friend or foe? The emergence and development of innovative and flexible financial startups is causing a revolution in financial markets by proving that financial services can be built from the ground up, in response to real user needs. So much so that gaining customers’ […]

[The Netflix Tech Blog] BigDataFr recommends: Innovating Faster on Personalization Algorithms at Netflix Using Interleaving

BigDataFr recommends: Innovating Faster on Personalization Algorithms at Netflix Using Interleaving […] The Netflix experience is powered by a family of ranking algorithms, each optimized for a different purpose. For instance, the Top Picks row on the homepage makes recommendations based on a personalized ranking of videos, and the Trending Now row also incorporates recent […]

[MIT Technology Review] BigDataFr recommends: Google Has Released an AI Tool That Makes Sense of Your Genome

BigDataFr recommends: Google Has Released an AI Tool That Makes Sense of Your Genome […] Almost 15 years after scientists first sequenced the human genome, making sense of the enormous amount of data that encodes human life remains a formidable challenge. But it is also precisely the sort of problem that machine learning excels at. […]

[Dataquest .io] BigDataFr recommends: Regular Expressions for Data Scientists

BigDataFr recommends: Regular Expressions for Data Scientists […] As data scientists, diving headlong into huge heaps of data is part of the mission. Sometimes, this includes massive corpuses of text. For instance, suppose we were asked to figure out who’s been emailing whom in the scandal of the Panama Papers — we’d be sifting through […]

[HAL] BigDataFr recommends: Predicting At-Risk Patient Profiles from Big Prescription Data

BigDataFr recommends: Predicting At-Risk Patient Profiles from Big Prescription Data Abstract […] We show how the analysis of very large amounts of drug prescription data make it possible to detect, on the day of hospital admission, patients at risk of developing complications during their hospital stay. We explore, for the first time, to which extent […]

[Datasciencecentral] BigDataFr recommends: Some Deep Learning with Python, TensorFlow and Keras

BigDataFr recommends: Some Deep Learning with Python, TensorFlow and Keras […] The following problems are taken from a few assignments from the coursera courses Introduction to Deep Learning (by Higher School of Economics) and Neural Networks and Deep Learning (by Prof Andrew Ng, deeplearning.ai). The problem descriptions are taken straightaway from the assignments. 1. Linear […]

[arXiv] BigDataFr recommends: A Big Data Analysis Framework Using Apache Spark and Deep Learning

BigDataFr recommends: A Big Data Analysis Framework Using Apache Spark and Deep Learning […] Subjects: Databases (cs.DB); Learning (cs.LG); Machine Learning (stat.ML) With the spreading prevalence of Big Data, many advances have recently been made in this field. Frameworks such as Apache Hadoop and Apache Spark have gained a lot of traction over the past […]

[Dataconomy] BigDataFr recommends: How big data technology is transforming fraud investigations

BigDataFr recommends: How big data technology is transforming fraud investigations […]The inside story of the Paradise Papers leak With more than 1,4 terabytes of data, the Paradise Papers is the illustration of the new possibilities for the fraud investigation world. Conducting investigations is a challenge in the age of big data. Massive volumes, unstructured and […]