Breaking into data science can be tough. Here are five tips to help you begin your journey.
Focus on new opportunities, be ready to say no to meetings, and document fiercely.
Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work.
A virtual machine is like having a computer inside your computer. Here’s how to create your own Linux VM.
The AI that powers deepfakes poses all sorts of questions for consumers of media. Using a couple of simple principles, though, you can develop a sophisticated understanding of what you’re looking at.
Gen Z data scientists are well suited to tackle bias in AI. Today’s leaders and practitioners need to lay the groundwork to enable them to do so.
Do you need to ditch your outliers? Here’s how to find (and remove) outliers in your data set with IQR.
To do any data science of value we need models that accurately represent our data set. Here’s how to evaluate a model’s fit to your training data.
In this step-by-step tutorial, I’ll show you how to automate your data analysis using a real-world problem.
Python scripts can automatically create and check the quality of regressions on your data sets. So what are you waiting for?
