data science

it’s possible to totally master every topic in data science? With data science covering such a broad range of areas — statistics, programming, optimization, experimental design, data storytelling, generative AI, to call a couple...

the k-NN Regressor and the thought of prediction based on distance, we now take a look at the k-NN Classifier. The principle is identical, but classification allows us to introduce several useful variants, reminiscent...

Introduction campaign you arrange for Black Friday was a large success, and customers start pouring into your website. Your Mixpanel setup which might often have around 1000 customer events an hour finally ends up...

to this “Advent Calendar” of Machine learning and deep learning in Excel. For Day 1, we start with the k-NN (k-Nearest Neighbors) regressor algorithm. And as you will notice, this is absolutely the best...

You wrote many beginner and explanatory articles on TDS. Has teaching the basics modified the way you design or debug real systems at work? I notice the correlation between the more I teach something, the...

Feature selection stays one of the vital critical yet computationally expensive steps within the machine learning pipeline. When working with high-dimensional datasets, identifying which features truly contribute to predictive power can mean the difference...

, it is rather easy to coach any model. And the training process is at all times done with the seemingly same method fit. So we get used to this concept that training any...

For SaaS (software as a service) corporations, monitoring and managing their product data is crucial. For individuals who fail to grasp this, by the point they notice an incident. Damage is already done. For...