Can InnerSource bring open source practices to closed corporate bureaucracies?
Open source won. Now, the OSS way of working is making inroads into new territories: the corporate engineering department.
Code for a Living
We’re here to help developers at every stage of their careers.
Level Up: Linear Regression in Python – Part 5
In the fifth lesson of the series we’ll learn how to build more flexible linear models by adding interaction and polynomial terms. We’ll fit and inspect our models both mathematically and visually to understand how they work. In the process, we’ll continue to practice our Python skills and discuss some of the merits (and drawbacks)…
Let’s enhance: use Intel AI to increase image resolution in this demo
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.
Level Up: Linear Regression in Python – Part 4
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…
Using low-code tools to iterate products faster
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.
Level Up: Linear Regression in Python – Part 3
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…
Level Up: Linear Regression in Python – Part 2
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…
How to prevent scope creep when managing a project from home
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.
How developers can be their own operations department
Many companies run parallel development and operations organizations. But what if you just ran one team that did both?
Level Up: Linear Regression in Python – Part 1
Linear regression is a machine learning technique for modeling continuous outcomes. It is used for both prediction and data analysis in a variety of different fields. It is also the basis for a number of other machine learning models, including logistic regression and poisson regression. For anyone who is interested in learning more about data…
Using Kubernetes to rethink your system architecture and ease technical debt
This is a story about trying to rethink complex systems: the challenges you face when you try to rebuild them, the burdens you face as they grow, and how inaction itself can cause it’s own problems. When you’re weighing the risk and reward of replacing architecture, it can take several attempts to find a solution that works for you.
