Geopandas introduction

If you are data analyst or data scientist working with python, then probably you are already familiar with pandas, but if you are entering a spatial domain data analytics you should check out GeoPandas. It extends panda’s capabilities by adding spatial operations and geometric types. In this blog I will …

Apache Spark basics

    In Big Data containers era, there is no way, that you will avoid working with cluster-computing frameworks, like Hadoop or Spark. At some point, I had to choose between those two, and as Apache spark seems to be more flexible and faster, I decided to look closer into it. Following …

Image recognition basics

There is multiple image classification datasets available online or embedded in python ML related modules, and this notebook contains just a sample code for image classification on those publicly available datasets. In this post, I will just use a very ‘blond’ solution and definitely not a perfect one (deep neural …

Protocol Buffers

“…Protocol buffers are Google’s language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from …