Understanding data structures and algorithms is still super important for making software. They're like the foundation for writing code that's quick and scales well, which helps you build better apps.

The bookshelf problem (which computer scientists call the “list labeling” problem) is one of the most basic topics in the field of data structures. “It’s the kind of problem you’d teach to freshman or ...

In this article, we document our experience developing PyExaFMM, a multithreaded Numba implementation of the fast multipole method, an algorithm with a nonlinear data structure and a large amount of ...

Schematics is a Python library to combine types into structures, validate them, and transform the shapes of your data based on simple descriptions. The internals are similar to ORM type systems, but ...

LeetCode isn’t a sprint; it’s a marathon. You won’t become a coding master overnight. It takes time, effort, and, most ...

Python really shines when it comes to automating repetitive tasks. Think about it: scanning networks, fuzzing applications, ...

The First Reinforcement Learning Tutorial Book with TensorFlow 2 Implementation Codes with both TensorFlow 2 and PyTorch 1 This is a tutorial book on reinforcement learning, with explanation of theory ...

Summary <p>Artificial intelligence (AI) techniques have been widely employed to monitor, control, and manage cyber&#x2010;physical power systems (CPPS). AI algorithms offer several advantages over ...