On LinkedIn, I regularly get the question on how one should get into data science. This is of course a very valid question but not very easy to answer as it depends on where you are now. To answer this question in the most general way I decided to spend a bit more time on this and write this guide.

There are many courses online which claim that you will become a data scientist after completion. When comparing these courses they mostly focus on the machine learning part. This is of course the part that seems the coolest, creating machine…

You probably have an idea of what variance is but did you ever realize that the variance and covariance have a geometric interpretation? Many algorithms such as logistic regression, support vector machines, and neural networks greatly benefit from zero-mean, standardized, and uncorrelated features. One method to investigate your dataset is calculating the variance-covariance matrix and this same matrix can be used to decorrelate your features.

The Jupyter notebook with all code is available here.

Before we start with the covariance let us first have a quick look at the mean and variance. These are two statistics we are generally interested…

In the last three months I wrote a Python course in 10 minutes bits a day called: learn Python 10 minutes a day. It was fun to write and I got many positive responses through my LinkedIn (which I really appreciate). I also get questions regularly, which I always try to answer.

Last week I got an interesting question from Domenico:

“𝙸𝚜 𝚝𝚑𝚎𝚛𝚎 𝚊 𝚒𝚗𝚍𝚞𝚜𝚝𝚛𝚢 𝚜𝚝𝚊𝚗𝚍𝚊𝚛𝚍 𝚏𝚘𝚛𝚖𝚊𝚝 𝚝𝚑𝚊𝚝 𝚢𝚘𝚞 𝚗𝚎𝚎𝚍 𝚝𝚘 𝚜𝚝𝚛𝚞𝚌𝚝𝚞𝚛𝚎 𝚢𝚘𝚞𝚛 𝙿𝚢𝚝𝚑𝚘𝚗 𝚙𝚛𝚘𝚐𝚛𝚊𝚖𝚜?“

I think this is a great question which can open a great discussion. As usual, the answer starts with ‘it depends’. …

Data science is hot and it seems that everybody is working on some sort of project involving the latest state-of-the-art (SOTA) algorithm. Of course with good reason as in many cases we can use data to give very reasonable prediction, almost in any field. While there is a lot of focus lately on SOTA algorithms, the simpler methods are sometimes forgotten.

Want to get started with Python? Start here!

Recently, I played around with a k-nearest-neighbor (KNN) algorithm and I was *amazed* how powerful it can be. The technique itself is used in many other fields. For example, I used…

This is a series of short 10 minute Python articles helping you to get started with Python. There are in total *25 lectures*, starting from the very basics, going up to more complex idioms. Feel free to contact me on LinkedIn for questions.

This is a sort of study guide which aims to create a plan through all the lectures. The lectures itself can be read within 10 minutes, however it is also important to do some hands-on practice. Depending on the lecture itself and your previous experience, these can also take a bit of time. While it can be…

This is a series of short 10 minute Python articles helping you to boost your knowledge of Python. I try to post an article each day (no promises), starting from the very basics, going up to more complex idioms. Feel free to contact me on LinkedIn for questions or requests on particular subjects of Python you want to know about.

Today is the 25th episode of learning Python 10 minutes a day. If you are here, you can be proud as we have discussed basic, intermediate, and a couple of advanced idioms of the Python language. More than enough to…

This is a series of short 10 minute Python articles helping you to boost your knowledge of Python. I try to post an article each day (no promises), starting from the very basics, going up to more complex idioms. Feel free to contact me on LinkedIn for questions or requests on particular subjects of Python you want to know about.

Yesterday, we talked about classes and how to use the object oriented programming (OOP) paradigm to address problems. The objects that we create can mimic real-life objects and the data and methods are all bundled inside the class. We also…

This is a series of short 10 minute Python articles helping you to boost your knowledge of Python. I try to post an article each day (no promises), starting from the very basics, going up to more complex idioms. Feel free to contact me on LinkedIn for questions or requests on particular subjects of Python you want to know about.

When getting a bit more into programming, one will come across two big paradigms: functional programming and object-oriented programming (OOP). Until now, what we mostly did is called functional programming. I have not yet found a satisfying all-round definition for…

Decorators is another confusing topic and their use can definitely feel somewhat magical. While the term to decorate a function is very appropriate, it also blurs a bit from what is happening, namely: wrapping a function inside another function. …

For new-comers, the lambda function can be somewhat intimidating. I have also avoided the use of these functions for some time as I never understood true use of them. Nowadays, I do see a benefit of the construct but it…

Data Scientist with a passion for natural language processing and deep learning. Python and open source enthusiast. Background in fluid dynamics.