[ArXiv] BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics

BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics […] Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful information to support […]

[Le Monde – Campus] BigDataFr recommande : « Data scientist est un métier qui demande énormément de neurones »

BigDataFr recommande : « Data scientist est un métier qui demande énormément de neurones » […] Selon le baromètre LinkedIn pour « Le Monde Campus », les jeunes diplômés en data science sont les profils les plus recherchés par les recruteurs français présents sur le réseau social. Serge Abiteboul, chercheur à l’Institut national de recherche […]

[HAL] BigDataFr recommande: Quels réseaux pour les Big Data?

BigDataFr recommande: Quels réseaux pour les Big Data? Résumé […] Un déluge de données est à prévoir dans les années à venir. Les utilisateurs de réseaux sociaux et l’Internet des objets, pour ne citer que ces deux exemples, génèrent déjà de grands volumes de données variées qui devront être transmises, enregistrées et traitées à grande […]

[Analyticsvidhya] BigDataFr recommends: 5 AI applications in Banking to look out for in next 5 years

BigDataFr recommends: 5 AI applications in Banking to look out for in next 5 years “Machine intelligence is the last invention that humanity will ever need to make.”, Nick Bostrom Artificial intelligence is a reality today and it is impacting our lives faster than we can imagine. It is already present everywhere, from Siri in […]

[ArXiv] BigDataFr recommends: Big Data Analysis Using Shrinkage Strategies

BigDataFr recommends: Big Data Analysis Using Shrinkage Strategies […] In this paper, we apply shrinkage strategies to estimate regression coefficients efficiently for the high-dimensional multiple regression model, where the number of samples is smaller than the number of predictors. We assume in the sparse linear model some of the predictors have very weak influence on […]

[Big Data à Paris : Inscrivez-vous !] 30 mai 2017 – @MATLAB Expo France #DataAnalytics #MachineLearning #bigdata #machinelearning

Événement Big Data : 30 mai 2017 – MATLAB Expo France, une journée unique pour le Data Analytics et le Machine Learning. Conférence gratuite – inscription obligatoire : cliquer ici Vous vous intéressez aux thématiques du Big Data, Machine Learning, aux algorithmes d’analyse prédictive ou encore aux avancées en matière de Deep Learning ? Venez […]

[SAS] BigDataFr recommends: Which machine learning algorithm should I use?

BigDataFr recommends: Which machine learning algorithm should I use? […] This resource is designed primarily for beginning data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is […]

[ArXiv] BigDataFr recommends: Best Practices for Applying Deep Learning to Novel Applications

BigDataFr recommends: Best Practices for Applying Deep Learning to Novel Applications […] This report is targeted to groups who are subject matter experts in their application but deep learning novices. It contains practical advice for those interested in testing the use of deep neural networks on applications that are novel for deep learning. We suggest […]

[Analyticsvidhya] BigDataFr recommends: 40 Questions on Probability for data science

BigDataFr recommends: 40 Questions on Probability for data science – [Solution: SkillPower – Probability, DataFest 2017] Introduction […] Probability forms the backbone of many important data science concepts from inferential statistics to Bayesian networks. It would not be wrong to say that the journey of mastering statistics begins with probability. This skilltest was conducted to […]