The world's first dataset aimed at improving the quality of English-to-Malayalam machine translation—a long-overlooked ...

Abstract: It is crucial to understand the several factors that contribute to a company's performance in the market in today's data-driven decision-making modern day. This study explores the ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

If there is one skill that sits at the heart of most successful AI and machine learning projects today, it is Python. Whether a company wants to build smarter automation, design predictive solutions, ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Experiment tracking is an essential part of modern machine learning workflows. Whether you’re tweaking hyperparameters, monitoring training metrics, or collaborating with colleagues, it’s crucial to ...