BigDataFr recommends: Getting into Data Science: A Guide for Students and Parents […] As can likely be expected, big data analytics is in the midst of an evolution. It’s a typical sight for nearly any new technology as experts and organizations get more used to all of its capabilities. Big data is certainly no exception […]
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[Dataconomy] BigDataFr recommends: http://dataconomy.com/simplifying-data-acquisition-augmentation/
BigDataFr recommends: Simplifying Data acquisition & augmentation […] As can likely be expected, big data analytics is in the midst of an evolution. It’s a typical sight for nearly any new technology as experts and organizations get more used to all of its capabilities. Big data is certainly no exception to these changes, especially as […]
[Analyticsvidhya – Tip] BigDataFr recommends: How to start applying for Analytics / Data Science Masters in the US Universities?
BigDataFr recommends: How to start applying for Analytics / Data Science Masters in the US Universities? […] Planning a masters program in data science in US? But, not completely aware of the application process? Or afraid of the application process? Don’t worry. I’m here to help. I will take you through the complete process required […]
[Analyticbridge] BigDataFr recommends: Internet Of Things (IOT) – A Privacy concern?
BigDataFr recommends: Internet Of Things (IOT) – A Privacy concern? […] [IoT] simply means for me all devices that are connected to internet forms part of global network, producing data, that can be utilize for the betterment of services or customer experience or the way one can use it, some examples Send real time alert, […]
[Informationweek] BigDataFr recommends: 12 Types Of Data IT Can’t Afford To Overlook
BigDataFr recommends: 12 Types Of Data IT Can’t Afford To Overlook Your organization probably already has more data than it knows what to do with. Yet, it’s quite likely you’re overlooking, disregarding, unaware of, or unable to access important information that could directly affect analyses and business outcomes. It doesn’t matter what your universe of […]
[HAL]] BigDataFr recommends: Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data
BigDataFr recommends: Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data Keywords: Nearest neighbor, Trajectory join, Big trajectory data, MapReduce. Abstract […] Trajectory data are prevalent in systems that monitor the locations of moving objects. In a location-based service, for instance, the positions of vehicles are continuously monitored through GPS; the trajectory of each vehicle […]
[O’R] BigDataFr recommends: 3 ideas to add to your data science toolkit
BigDataFr recommends: 3 ideas to add to your data science toolkit I’m always on the lookout for ideas that can improve how I tackle data analysis projects. I particularly favor approaches that translate to tools I can use repeatedly. Most of the time, I find these tools on my own—by trial and error—or by consulting […]
[Datasciencecentral] BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Full – #iot
BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Part 1 and 2 […] This two part blog is based on my forthcoming book: Data Science for Internet of Things. It is also the basis for the course I teach Data Science for Internet of Things Course. I will be […]
[Datasciencecentral] BigDataFr recommends: Ableism in the Numbers – Social Metrification #datascientist
BigDataFr recommends: Ableism in the Numbers – Social Metrification […] Ableism (able + ism) is apparent in many interactions between people. While driving on a road having a posted limit of 60 KPH, I was traveling slower since I expected a red light to soon appear ahead of me. The driver behind me – at […]
[CIO] BigDataFr recommends: How to hire for the right big data skill set
BigDataFr recommends: How to hire for the right big data skill set Data science is a hot new industry, but what skills and background do you need to break into the field? Essentially, data science, data engineering and data analytics are broad — and sometimes ambiguous — terms that describe a litany of skills and […]