[IBM] BigDataFr recommends: Developing the big data and analytics maturity model #datascientist

BigDataFr recommends: Developing the big data and analytics maturity model ‘A recent posting introduced and described the big data and analytics maturity model. The model provides a framework for a coherent approach to big data and analytics across an enterprise, one that is business-driven and able to adapt to evolving business objectives. The model has […]

[Sethbling] BigDataFr recommends: MarI/O – Machine Learning for Video Games #machine-learning

BigDataFr recommends: MarI/O – Machine Learning for Video Games MarI/O is a program made of neural networks and genetic algorithms that kicks butt at Super Mario World. YouTube:  youtube.com/sethbling Twitter:  @SethBling Facebook: facebook.com/sethbling http://sethbling.com/ Source Code: http://pastebin.com/ZZmSNaHX [MIT Press Journal] BigDataFr recommends: Evolving Neural Networks through Augmenting Topologies Abstract An important question in neuroevolution is how to […]

[arXiv] BigDataFr recommends: Big Data Analytics in Bioinformatics – A Machine Learning Perspective #machine-learning

BigDataFr recommends: Big Data Analytics in Bioinformatics – A Machine Learning Perspective ‘Bioinformatics research is characterized by voluminous and incremental datasets and complex data analytics methods. The machine learning methods used in bioinformatics are iterative and parallel. These methods can be scaled to handle big data using the distributed and parallel computing technologies. Usually big […]

[Forbes] BighDataFr recommends: Spark Or Hadoop – Which Is The Best Big Data Framework? #datascientist #hadoop #apache spark #machine-learning

BigDataFr recommends: Spark Or Hadoop – Which Is The Best Big Data Framework? One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are not directly comparable […]

[MIT Digital Programs] BigDataFr recommends: Tackling the Challenges of Big Data #datascientist #machine learning #hadoop

  recommends: MIT’s Digital Program -Tackling the Challenges of Big Data’ New Session!  Tackling the Challenges of Big Data, running July 7 – August 18 « This Digital Programs course will survey state-of-the-art topics in Big Data, looking at data collection (smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting […]

[JDN] BigDataFr recommande : Big Data, la 3eme phase #hadoop

BigDataFr recommande : Big Data, la 3eme phase « Avant Internet, c’est-à-dire pendant les années 70 et 80, les passionnés d’informatique et les chercheurs qui devaient déplacer des fichiers utilisaient le sneaker-net  ou « réseau-basket »[1] Avec l’avènement du Big Data, ce réseau fait son grand retour. un nombre croissant d’entreprises parmi les plus importantes et […]