Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

Linux has become one of the largest operating systems on the servers that run large websites, and hopefully, one day, it will be big in the desktop market too. Some of you may know how Linux as an ...

Much of modern operating system functionality happens in and around the kernel. That’s a problem when you’re implementing monitoring and observability tools or adding low-level security tools because ...

In Linux kernel programming, there are numerous occasions when processes wait until something occurs or when sleeping processes need to be woken up to get some work done. There are different ways to ...

Nobody loves a reboot, especially not if it involves a late-breaking patch for a kernel-level issue that has to be applied stat. To that end, three projects are in the works to provide a mechanism for ...

Configuration is the first step in building a kernel. There are many ways and various options to choose from. The kernel will generate a .config file at the end of the process and generate a series of ...