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In an era where data drives decision-making across industries, geospatial data analysis has emerged as a critical tool for understanding our world in a whole new dimension. From urban planning to disaster management, geospatial data allows for deeper insights into phenomena and events than ever before. In this article, we will take a closer look […]

While many consider the technology to still be in its infancy, geospatial AI solutions have already demonstrated the ability to automate many manual processes and provide analyses far more quickly and more accurately than humans can, while using fewer resources – given the right conditions. In this article, we will discuss geospatial AI use cases […]

The basis of all machine learning projects is data collection and acquisition. But that is also the first stumbling block where many ML projects fail. In this article, we will discuss the challenges of text, audio, photo, and video data collection for ML training models so that you can predict and avoid the many pitfalls. […]

Spatial data is so ever-present that we tend to forget about its significance – from the simplest of maps to weather forecasts to GPS – all of this is based on spatial data. Spatial data science simply takes this to the next level – utilizing data science techniques and methods to use spatial data in […]

Named entity recognition (NER) is vital to natural language processing (NLP)

Despite fears of AI taking over the world, at its core, AI is still reactionary and doesn’t truly learn on its own. It can only make predictions based on the data it’s given. That is why data quality for machine learning and AI should be at the core of every project. Without high-quality training data, […]