BigDataFr recommande : Les 3 bugs majeurs du big data Et s’il y avait un mirage du big data ? Et si le Big Data ne tenait pas toutes ses promesses, notamment celles avancées par certains cabinets de conseil ? Il faut dire que les modèles centrés sur l’analyse quantitative des données souffrent de nombreuses […]
Author: Big Data
[Dataconomy – View] BigDataFr recommends: How will data science change in 2016
BigDataFr recommends: How will data science change in 2016? 2015 was a good year for data science. A cursory glance at any tech jobs board reveals the sheer breadth of companies looking for data science expertise. Technical terms such as machine learning are slowly entering the public consciousness. Many people still don’t realise how much […]
[Quora – Tips] BigDataFr recommends: What are 20 questions to detect fake data scientists?
BigDataFr recommends: What are 20 questions to detect fake data scientists? Identifying the essential skills for data scientists. I’ll stay away from code examples myself as they seem rather shop-specific and thus best designed locally, but if you want some questions, here you go. These questions are intentionally difficult and are more on the statistics/modeling […]
[analyticsvidhya – Tutorial] BigDataFr recommends: A Comprehensive guide to Data Exploration #machinelearning
BigDataFr recommends: A Comprehensive guide to Data Exploration Introduction There are no shortcuts for data exploration. If you are in a state of mind, that machine learning can sail you away from every data storm, trust me, it won’t. After some point of time, you’ll realize that you are struggling at improving model’s accuracy. In […]
[Capital] BigDataFr recommande : Big data – comment les géants du Net transforment nos faits et gestes en juteux business
BigDataFr recommande : Big data – comment les géants du Net transforment nos faits et gestes en juteux business C’était le deal de départ. Internet, c’est gratuit, mais, en échange, l’utilisateur doit naviguer entre les pubs. Sauf qu’avec la numérisation massive de la vie quotidienne – e-mails, recherches sur Google, «likes» sur Facebook, photos sur […]
[O’R] BigDataFr recommends: How to think like a data scientist #datascientist
BigDataFr recommends: How to think like a data scientist Identifying the essential skills for data scientists. Data science is about finding signals buried in the noise. It’s tough to do, but there is a certain way of thinking about it that I’ve found useful. Essentially, it comes down to finding practical methods of induction, where […]
[McKinsey] BigDataFr recommends: Digital America – A tale of the haves and have-mores
BigDataFr recommends: Digital America – A tale of the haves and have-mores Digital capabilities, adoption, and usage are evolving at a supercharged pace. While most users scramble just to keep up with the relentless rate of innovation, the sectors, companies, and individuals on the digital frontier continue to push the boundaries of technology use—and to […]
[Sciences et Avenir] BigDataFr recommande : Les Big data vont révolutionner nos vies, notre travail et notre pensée
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, […]
[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 […]