BigDataFr recommends: Data is the first class citizen Algorithms and models are just helpers – Interview with Dato’s Alice Zheng What project have you worked on do you wish you could go back to, and do better? I think that pretty much applies to any project you do as a data scientist. When you’re developing […]
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[Datasciencecentral] BigDataFr recommends: Predicting the Future #datascientist
BigDataFr recommends: Predicting the Future TOne of the really fun aspects of being a data scientist is that we are called upon to predict the future. Frequently that means trying to predict who will buy, who will churn, what they will buy next, how much they will spend, all the sorts of questions that are […]
[arXiv] BigDataFr recommends: Privacy by design in big data: An overview of privacy enhancing technologies #datascientist
BigDataFr recommends: Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics The extensive collection and processing of personal information in big data analytics has given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling, and disclosure of private data. To reap the […]
[CIO] BigDataFr recommends: Cybersecurity dream-come-true or pipe dream? #machinelearning
BigDataFr recommends: Machine learning: Cybersecurity dream-come-true or pipe dream? A Want to know which of your workers aren’t working much, which ones are planning to leave soon and/or might also be planning to steal some proprietary data on the way out the door? Machine learning can help you spot it much more quickly than your […]
[O’R] BigDataFr recommends: Beyond the Venn diagram #datascientist
BigDataFr recommends: Beyond the Venn diagram Identifying the essential skills for data scientists. If you work at a company where the core asset is data, then you know how hard it is to hire data scientists. Indeed, we’ve heard for years about a shortage of data scientists. The last few years have seen a proliferation […]
[Le Parisien] BigDataFr recommande : Masters : ces diplômes qui valent de l’or
BigDataFr recommande: Masters : ces diplômes qui valent de l’or […]L’explosion des données numériques s’impose comme un enjeu central pour les entreprises : comment gérer et analyser ces mégadonnées, venant notamment des réseaux sociaux, pour en tirer le meilleur parti ? Le Big Data devient ainsi un « véritable enjeu stratégique et économique », rappelle […]
[Analyticsvidhya] BigDataFr recommends: Important Job Roles in Data Science Industry Today – Who Does What ?
BigDataFr recommends: Important Job Roles in Data Science Industry Today – Who Does What ? Introduction One evening, I was catching up with a friend over a few drinks – let’s call him Jon (name changed). He seemed determined to become a data scientist and was charting out his career plan accordingly. I quizzed him […]
[Dataconomy] BigDataFr recommends: Data is the first class citizen – Algorithms and models are just helpers
BigDataFr recommends: Data is the first class citizen Algorithms and models are just helpers – Interview with Dato’s Alice Zheng What project have you worked on do you wish you could go back to, and do better? Too many! The top of the list is probably my PhD thesis. I collaborated with folks in software […]
[Informationweek – Tips] 8 Ways You’re Failing At Data Science #datascientist
BigDataFr recommends: 8 Ways You’re Failing At Data Science Data science would be easier to comprehend if there were a standard definition of it. True data science comprises several disciplines, including mathematics, statistics, machine learning, and computer science. A data science team must also understand how to curate and prepare data, analyze it, and present […]
[arXiv] BigDataFr recommends: Scalable and Accurate Online Feature Selection for Big Data
BigDataFr recommends: Scalable and Accurate Online Feature Selection for Big Data Feature selection is important in many big data applications. There are at least two critical challenges. Firstly, in many applications, the dimensionality is extremely high, in millions, and keeps growing. Secondly, feature selection has to be highly scalable, preferably in an online manner such […]