Overview  GitHub repositories provide hands-on learning of real-world MLOps workflows.Tools like MLflow, Kubeflow, and DVC show how scaling and tracking wo ...

We’ve put together a guide that breaks down the basics, from what Python is all about to how you can actually start using it. You can even grab a python tutorial pdf to have handy. So, whether you’re ...

Objective: A simple and well-designed template structure to start a machine learning/deep learning-based project. The template provides a basic directory structure with additional files (like examples ...

This book is edited by Li Hui and Chen Yanyan, with associate editors Yang Yu, Gao Yong, Zhang Qiaosheng, Bi Ye, and Liu Dengzhi. It is rich in content, covering 32 theories and 32 practical cases, ...

Abstract: Neural network models of machine learning have shown promising prospects for visual tasks, such as facial emotion recognition (FER). However, the generalization of the model trained from a ...

Overview Strong basics in math, programming, and statistics drive faster AI progressReal projects teach problem-solving better than endless tutorialsData qualit ...

This review explores the recent advancements in enhancing Computational Fluid Dynamics (CFD) through Machine Learning (ML). The literature is systematically classified into three primary categories: ...

Theoretical and computational chemistry (TCC) is a set of theories and models that, over the years, were refined to the point that it is possible to determine measurable quantities with precision, ...

Abstract: Money laundering is a profound global problem. Nonetheless, there is little scientific literature on statistical and machine learning methods for anti-money laundering. In this paper, we ...