Across alien epics and procedural crime dramas, detectives and truth seekers have repeated the mantra: zoom and enhance. It’s passed into popular culture as a much-beloved meme, but in recent years, machine learning has increasingly made this fiction trope into an accessible reality. And we've got the demo to prove it.
In the fourth lesson of the series, we’ll talk about the matrix representation of the linear regression problem. In the process, we’ll discuss the basics of matrix multiplication. We’ll also see how this mathematical understanding can prepare us to make sense of error messages that we might encounter when fitting a model in Python. Here…
Many developers are skeptical of using low-code tooling to build software. Buying software instead of building it has advantages, especially when your goal is to iterate faster.
The Stack Overflow Podcast is a weekly conversation about working in software development, learning to code, and the art and culture of computer programming.
We put our finger the pulse of what's drawing the kids into the wide world of code.Listen now
Content written by developers, for developers, is a booming business.Listen now
We chat with Innocent Ndubuisi-Obi and Luke Jordan about the unique challenges you face when trying to solve civic problems with software.Listen now
As our applications move from local hardware to a sprawling array of clouds and containers, figuring out how they behave and what's gone wrong is key.Listen now
In the third lesson of the series, we’ll implement our first linear regression model with multiple predictors (this is called “multiple linear regression”). As an example, we’ll use a simulated dataset to predict student quiz scores. In the process, we’ll again practice our graphing and Python skills. Here are some Stack Overflow questions related to…
This morning, Prosus (PROSY) has announced its intention to acquire Stack Overflow for 1.8 billion dollars. This is tremendously exciting news for our employees, our customers, our community members, and for our shareholders, and I will share a bit more about what it all means.
Stack Overflow celebrates site accomplishments with confetti in multiple places. That means it's time to formalize it in our design system.
In the second lesson of the series, we’ll learn how to fit and interpret a simple linear regression with a categorical predictor. We’ll use a simulated dataset to predict the amount of time someone will spend on a website based on the browser they are using. We’ll also predict the rental prices of NYC apartments…
When unexpected changes are requested during the development process, your final product may be a lot more complicated than what your spec originally called for. This phenomenon is called “scope creep.” Add a fully remote team with thin work-life boundaries on top of that, and you've got problems.