Hands-on Tutorials

Searching for Related Organizations Addresses with Web-Search, spaCy, and RegEx

Problem Statement

Recently, one of our clients has contacted us with an interesting problem. It was an investment company, which needed to calculate potential risks for their objects of investment. They required a solution that would help generate a list of all addresses (or GPS coordinates) that were associated with a specific company name. The problem our client faced was that a lot of companies could have many different subdivisions with different names in different languages. Plus, a lot of companies have departments all over the world. …

Hands-on Tutorials

A baseline approach to detecting documents in images for further processing — Optical Character Recognition, Document Type Detection, Named Entity Extraction and similar tasks.

Photo by Daniil Silantev.


Object detection and extracting, especially with semantic segmentation, is a well-studied problem with a developed set of almost standard solutions. So if you’re a seasoned data scientist, most likely you won’t find anything new or special in this article. But if you’re relatively new to data science and image processing, in particular, this article may become your practical tutorial on making your first semantic segmentation model. Please note, that we’re not going to discuss any theoretical basis for semantic segmentation. This is only an example of a code\solution that was developed as a baseline approach during a proof of concept.

LIDAR data for power line detection


In recent years, there was great progress in the development of LIDAR detectors that resulted in huge amounts of raw data. LIDARs are now more accurate and provide a much higher resolution than even 10 years ago. Aerial-based LIDARs have become an efficient method for receiving information about the environment. Nevertheless, the data you get is in fact only a collection of sparse points that may provide some nice visualization but require extensive processing when it comes to more practical purposes. Unfortunately, as of now, the progress of computer vision mostly concerns structured two-dimensional data (photo, video). The current methods…

Alex Simkiv

Data Scientist @ MindCraft.ai. Mastering data-driven solutions from data insights.

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