During the end of September 2020, we participated in the Copernicus Hackathon Sweden 2020. At the hackathon - organized by Arctic Business and Innovatum Startup - all participating teams made use of satellite images through the European Copernicus project to tackle various problems related to climate change, life on land, and COVID-19.
In this blogpost, we will look at how we solved the problem of detecting snow and clouds in real world satellite images using deep learning.
The hackathon offered challenges addressing problems varying from water scarcity to automatic field delineation to COVID-19. We chose the Snow and Cloud Detection…
Every time we express ourselves, either verbally or in written text, these expressions carry a lot of information. What subjects we talk about, if we express opinions or facts, our selection of words etc., all of which add some kind of information to our expressions, and can be interpreted and extracted to gain insights.
With all the web content in terms of e.g. consumer reviews and social media posts we have today, companies now have access to tons of useful information that can help improve their business. In most cases however, the huge amount of data available is not manageable…
One of the most powerful techniques for building predictive Machine Learning models is the Gradient Boosting Machine. Gradient boosting is widely used in both industry and by Machine Learning competition winners, and the method can be used for a lot of different problems like regression, binary classification and multi-class classification. In this post, we will turn our focus to gradient boosting and try to get an understanding of what this algorithm does and how it works, as well as applying gradient boosting to the Titanic disaster dataset, using the gradient boosting framework LightGBM.
The Titanic disaster dataset…
Data Scientist at Backtick Technologies