An overview of what DevOps and MLOps have in common and what are their differences (if any) — About ten years ago, the community realized that there was a barrier between the delivery and operations teams. On the one hand, there was the development team, which was responsible for writing and testing the code. On the other hand, the operations team should make the code run in production…

A practical example of performing data cleaning using the popular Python library. — Data Cleaning is one of the mandatory steps when dealing with data. In fact, in most cases, your dataset is dirty, because it may contain missing values, duplicates, wrong formats, and so on. …

A step-by-step tutorial on how to use warm_start=True and partial_fit() in scikit-learn — When you build a Machine Learning model from scratch, usually, you split your dataset into training and test set, and then you train your model on your training set. …

Some tips with a practical example on how to wrap your Data Science Project in a Docker image and run it in a Docker container — When writing the code for a Data Science project, it should be portable as possible, that is, that it can be executed as many times as you want even on different machines. It often happens that a Data Science project works correctly on your machine, during the modeling and testing…

An overview of the ipyvizzu library, with a practical example. — Communicating the results of an analysis is one of the required skills for a Data Scientist. One possible strategy to communicate results is the use of animations, which can help the audience quickly get the point and assimilate the message you want to convey. Recently I have discovered and tested…