Claude AI Guide: Mastering Haiku, Sonnet and Opus

Build custom tools and automate daily workflows with this complete Claude AI course. Includes prompt engineering and Opus 4.6 ...
marktechpost

A Coding Guide Implementing SHAP Explainability Workflows with Explainer Comparisons, Maskers, Interactions, Drift, and Black-Box Models

In this tutorial, we implement SHAP workflows as a practical framework for interpreting machine learning models beyond basic feature-importance plots. We start by training tree-based models and then ...
marktechpost

A Coding Tutorial on Datashader on Rendering Massive Datasets with High-Performance Python Visual Analytics

In this tutorial, we explore Datashader, a powerful, high-performance visualization library for rendering massive datasets that quickly overwhelm traditional plotting tools. We work through its full ...
C&EN

Benchmarking Swaths of Intermolecular Interaction Components with Symmetry-Adapted Perturbation Theory

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
Europe PMC

PyMC: a modern, and comprehensive probabilistic programming framework in Python.

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax ...