Abstract: Undersampling is one of the most popular techniques for dealing with class-imbalance problems. Various undersampling methods have emerged over the past few decades. Each of them exhibits the ...

A practical roadmap for data science beginners, covering fundamentals, key libraries, projects, and advanced skills. It focuses on real-world learning, avoiding common mistakes, and building job-ready ...

The Facebook Business SDK is a one-stop-shop to help our partners better serve their businesses. Partners are using multiple Facebook API's to serve the needs of their clients. Adopting all these ...

Python dataclasses work behind the scenes to make your Python classes less verbose and more powerful all at once. Here's an introduction to using dataclasses in Python. Everything in Python is an ...

Self-driving laboratories (SDLs), powered by robotics, automation and artificial intelligence, accelerate scientific discoveries through autonomous experimentation. However, their adoption and ...

Abstract: Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional ...

We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

As AI engineers, crafting clean, efficient, and maintainable code is critical, especially when building complex systems. Let’s explore some key design patterns that are particularly useful in AI and ...

Typical quests in materials science, as for instance finding stable compositions of an alloy and its properties, or determining the conditions for molecular adsorption on a surface, involve ...