Author: Zuzanna Kwiatkowska Scientific collaboration: Mateusz Rapicki   Have you ever wondered how many things must happen during your 15-minute-long visit to the doctor’s office? Imagine yourself walking into the room. You sit down, and the doctor asks you what the reason for your visit is. They listen to you and ask about your medical history and any information relevant to your problem. Maybe they already have some of that information in their computer files, so they must read them and recollect everything about your case. Or worse – you bring that information with you in a potentially chaotic stack

Author: Adam G. Dobrakowski Redaction: Zuzanna Kwiatkowska   If you work in machine learning, you’ve definitely heard about A/B testing. It is the best and most reliable experiment which you can conduct to confirm the performance and quality of your model. In this post, I’m going to introduce you to the topic of A/B testing and what steps they involve. It is the first out of 3 post in this series:   A/B Testing in Machine Learning. Part 2: Most common problems A/B Testing in Machine Learning. Part 3: 4 most common mistakes   What are A/B tests?   Originally,

Author: Adam G. Dobrakowski Redaction: Zuzanna Kwiatkowska   In Machine Learning, benchmark is a type of model used to compare performance of other models. There are different types of benchmarks. Sometimes, it is a so-called state-of-the-art model, i.e. the best one on a given dataset for a given problem. The goal of benchmarking is then to see if we can create a better model and beat published results. However, in this article, I want to talk about a simple benchmark, which you create in the very beginning of your project. Its goal is to track our progress and see how

Author: Adam G. Dobrakowski Redaction: Zuzanna Kwiatkowska   Since I started working on Machine Learning projects a couple of years ago, I decided to build a cheatsheet with the most important commands to use on a day-to-day basis. Most of them are used so rarely that they are hard to remember. On the other hand, after a short time, I realised that I’m looking for the same information on Stack Overflow over and over again. That’s why in this short article, I would like to share with you a part of my cheatsheet. I hope that it is going to

Author: Adam G. Dobrakowski Redaction: Zuzanna Kwiatkowska   There is a simple way to analyse (almost) any tabular data in less than 2 minutes in a simple and efficient way. I will show you how to do it using only 2 Python tools: Jupyter notebook and Pandas profiling. No matter what our problem is, if the solution requires implementation of some machine learning model, we always have to start with data analysis. Let’s say we have a single table, where rows represent observations (for example people we analyse), and the columns represent their features (for example age, height, gender, etc.).

  Authors: Jakub Podolak, Krzysztof Chartanowicz   Every executive and marketing specialist knows how challenging it is to choose the best ad when managing multiple advertising campaigns. When you want to showcase your product using a visual ad, you want to choose one that gives you the highest possible performance, discarding the ones that are not engaging enough. One of the most popular performance metrics is the Conversion Rate (CR). It measures how many views of the ad resulted in an action which was significant for the business (for example in a sale). The more engaging the ad, the higher