Why write ten lines of code when one will do? From magic variable swaps to high-speed data counting, these Python snippets ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...

Abstract: In this paper, forecasting algorithms were tested on renewable energy production data and their comparative analysis was carried outThe machine learning methods that were used in the work ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Getting input from users is one of the first skills every Python programmer learns. Whether you’re building a console app, validating numeric data, or collecting values in a GUI, Python’s input() ...