Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: With the innovative application of machine learning neural networks, the problem of feature extraction and dimensionality reduction in big data processing has received extensive attention, ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

1 Rice Research Institute, Guangdong Academy of Agricultural Sciences/Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), ...

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.

Important Note: This project explores quantum-inspired algorithms using classical implementations. All code is research-grade, not production-ready. Hybrid methods combine tensor operations with ...

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 ...

Abstract: In recent times, the increase in the human population has led to a growing demand for food. In response to this increasing demand, smart farming systems are being developed to enable ...