Category: Data Science

I have been working in a “Data Science” consulting team for 8 months now. Before that I got a Master’s degree in Computer Science with a machine learning specialization. So I could argue that I have seen both sides of the coin here and I have noticed some differences. Disclaimer: You will have trouble finding…… Continue reading How is Data Science different from Machine Learning?

Consulting can be a frustrating business to enter into as a newcomer. Because every time you ask a consultant a question about their typical work, they tend to answer with “It depends.” Because a lot of our day-to-day depends on the specific data science consulting project but also on the client. So after recently completing…… Continue reading First project as a Data Science Consultant: tasks, tools, meetings

What do I want to learn this month? I liked doing this last month, so let’s continue this tradition of sharing my study goals for now. Quick context, I already have university degrees and I started a job in January in Data Science that I enjoy, so my goals are largely internally motivated. The number…… Continue reading Machine Learning Study Goals – August 2022

Many models in machine learning don’t work with categorical data. So what do we do in that case? Of course you can always just remove them, but you would lose a lot of valuable information. So in this post, I share how you can use one hot encoding to make that information usable. I stumbled…… Continue reading One Hot Encoding – How to deal with categorical data in Machine Learning

You have probably heard of the train-test-split in the context of machine learning, which is fairly intuitive. Show some examples to your model, let it learn and then test it on other examples. But there is one more data split that is used and that is the train-validation-test split or sometimes achieved by using cross-validation.…… Continue reading What is validation data used for? – Machine Learning Basics