Abstract: Machine learning (ML) with approximation and numerical simulations plays an important role in aircraft design. ML techniques, such as deep learning and reinforcement learning, are ...

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., ...

Introduction: Cardiovascular disease (CVD) remains the leading global cause of mortality, with hypertension (HT) being a significant contributor, responsible for 56% of CVD-related deaths. Masked ...

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 ...

Google Colab, also known as Colaboratory, is a free online tool from Google that lets you write and run Python code directly in your browser. It works like Jupyter Notebook but without the hassle of ...

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: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...

Machine learning can enhance ARF outcome predictions but faces challenges like data quality, system heterogeneity, and clinician acceptance. High ARF mortality and mechanical ventilation risks ...

Introduction: Middle-aged and older adults are highly susceptible to depression. For this reason, early identification and intervention can substantially reduce its prevalence. This study innovatively ...