BigDataFr recommande: Les Big data vont révolutionner nos vies, notre travail et notre pensée Le professeur Viktor Mayer-Schönberger alerte sur la « mise en données du monde » favorisée par l’accumulation de « data ». Sciences et Avenir : Dans votre ouvrage, vous citez le chiffre de 1, 7 milliard par jour d’emails, appels téléphoniques, et autres communications (Skype, […]
Month: janvier 2016
[Video Big Data BPIFrance] BigDataFr recommande : Les PME à l’assaut du Big Data
BigDataFr recommande : Les PME à l’assaut du Big Data : Les Vidéos Pour casser les idées reçues et convaincre les PME du potentiel du Big data, Bpifrance a organisé le 03 novembre dernier une journée thématique : « les PME à l’assaut du Big Data ». Nous avons eu l’opportunité de vous recommander cette […]
[analyticsvidhya] BigDataFr recommends: 8 Proven Ways for improving the “Accuracy” of a Machine Learning Model #machinelearning #datascientist
BigDataFr recommends: 8 Proven Ways for improving the “Accuracy” of a Machine Learning Model Introduction Enhancing a model performance can be challenging at times. I’m sure, a lot of you would agree with me if you’ve found yourself stuck in a similar situation. You try all the strategies and algorithms that you’ve learnt. Yet, you […]
[Forbes] BigDataFr recommends: Big Data -12 Amazing Highs And Lows Of 2015
BigDataFr recommends: Big Data – 12 Amazing Highs And Lows Of 2015 2015 was a tumultuous year for Big Data, with highs continuing to dazzle us with the potential world-changing power of data and analytics. At the same time there were plenty of lows serving as ongoing warnings that much is still unknown about exactly […]
[BPI] BigDataFr recommande : Les PME à l’assaut du Big Data : le Best-Off
BigDataFr recommande : Les PME à l’assaut du Big Data : le Best-Off Voir les autres vidéos Pour casser les idées reçues et convaincre les PME du potentiel du Big data, Bpifrance a organisé le 03 novembre 2015 une journée sur le thème « les PME à l’assaut du Big Data ». Revivez en vidéo […]
[Dataconomy] BigDataFr recommends: The Data Science Industry: a look at the key roles
BigDataFr recommends: The Data Science Industry: a look at the key roles Re-identifying the roles in the Data Science Industry Data Science is a growing field, that goes without saying. Businesses are taking a data driven approach to maximize understanding, output and results within their industry, gaining a competitive advantage. Although, the end goal for […]
[arXiv] BigDataFr recommends: Strategies and Principles of Distributed Machine Learning on Big Data #datascientist
BigDataFr recommends: Strategies and Principles of Distributed Machine Learning on Big Data ? The rise of Big Data has led to new demands for Machine Learning (ML) systems to learn complex models with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics thereupon. In order to […]
[Datasciencecentral] BigDataFr recommends : How to Raise a Data -Scientist in the Xbox Age
BigDataFr recommends: How to Raise a Data -Scientist in the Xbox Age An article by this title (without the ‘Data’) appeared in December in the WSJ written by Robert Scherrer, Chairman of the Physics and Astronomy department at Vanderbilt University. As an educator and parent he has some interesting and humorous insights into how to […]
[HAL] BigDataFr recommends: Large Interactive Visualization of Density Functions on Big Data Infrastructure
BigDataFr recommends: Large Interactive Visualization of Density Functions on Big Data Infrastructure Abstract Recently, hybrid multi-site big data analytics (that combines on-premise with off-premise resources) has gained increasing popularity as a tool to process large amounts of data on-demand, without additional capital investment to increase the size of a single datacenter. However, making the most […]
[Informationweek] BigDataFr recommends: Algorithms – Turning Data Into Products
BigDataFr recommends: Algorithms – Turning Data Into Products Blame Persian mathematician Al-Khwarizmi. Around 825 AD, he wrote a book entitled « Al-Khwarizmi on the Hindu Art of Reckoning, » basically a math book using the numbers we use today. It was translated into Latin as « Algorithmi de numero Indorum. » From this, we get our current word « algorithm ». […]