In the field of Machine Learning there are multiple models whose internal structure makes it non-trivial to understand the why behind the decisions it makes. This set of models are widely known as black box models and are usually very…
In a previous article, we gave a theoretical introduction to Spark Structured Streaming where we analysed in depth the high-level API that Spark provides for processing massive real-time data streams (Structured Streaming). There, we looked at the essential theoretical concepts…
In recent years, data processing with low latency, practically in real time, is becoming a requirement increasingly demanded by companies in their big data processes. It is in this context where the concept of stream processing is introduced, which refers…
The linear regression model is one of the most useful tools in every data scientist’s kit bag. Although this post is geared towards people with first-hand knowledge of this statistical model, it never hurts to remember that linear regression aims…
Function overloading is a very interesting tool that allows several different functions to share the same identifier, improving the readability and interpretability of our code in some scenarios. This tool is available by default in many of today’s most widely…
In a previous blog article, we analyzed from a theoretical point of view which are the main libraries for data science and machine learning used by data scientists to treat data efficiently and extract its full potential. In this post,…