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02/09/2020
reading time 4 minutes
At namR, we gather publicly available, non-personal data and use our AI tools to build a Digital Twin of France. In that regard, we need a robust and scalable scraping infrastructure. Until recently, we were using Scrapy but, reaching its limits, we started developing our own solution, based on Celery.
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16/05/2019
reading time 4 minutes
One of the most important aspects of our work at namR is to find, clean, aggregate and organise large datasets of geolocalised data found in Open Data portals. Very often the same geographical area or object is described in many different datasets, each containing a different piece of information.
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reading time 8 minutes
At namR we are working hard to build the Digital Twin of France. To this end, we use a lot of sources of information such as aerial images. Extracting useful information from the unstructured data that are images? Sounds like a job for the computer vision team!
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reading time 5 minutes
There is no secret that when dealing with aerial images the best state-of-the-art results are achieved with deep learning models which come at the cost of their complexity. At the same time thanks to the Open Data, we can explore in a creative way even the most sophisticated techniques.
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14/05/2019
reading time 7 minutes
Private and public open data, social network data, private data platforms... The web is an infinite source of external data. It comes in a variety of formats: data tables, geolocated data, APIs, images and text. How can organisations take advantage of all the value to be gained from big data processing?
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about nam.R

nam.R is a data & deep-tech company, specialized in geolocated intelligence, building a digital representation of the physical world. nam.R aims at providing easy-to-use and actionable data to public and private organisations to massify and optimise their actions, investments and projects. 

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