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Abstract: Most of the content on various social media platforms has enormous textual data. Before being used in machine learning models, this textual data must be transformed into numerical formats ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

Deep learning methods such as multilayer perceptrons (MLPs) and convolutional neural networks (CNNs) have been applied to predict the complex traits in animal and plant breeding. However, it remains ...

Deep learning methods such as multilayer perceptrons and convolutional neural networks have been applied to predict the complex traits in animal and plant breeding. However, it remains challenging to ...

What is Data Science Fundamentals with Python? Data science transforms information into action. Through programming, analytics, and machine learning, data professionals uncover patterns, generate ...

Introduction: Accurately predicting the on-target activity of sgRNAs remains a challenge in CRISPR-Cas9 applications, due to the limited generalization of existing models across datasets, small-sample ...

1 Hunan Provincial Key Laboratory of Finance and Economics Big Data Science and Technology, Hunan University of Finance and Economics, Changsha, China 2 College of Information Science and Engineering, ...

Freeze casting is a versatile manufacturing process for producing porous materials with tailored microstructures and properties. However, due to the complexity and variability involved, predicting ...

Sabrina Carpenter has returned to the top of the charts with her latest single “Manchild” debuting at Number One on the Billboard Hot 100. “If I really wanted to, I could have stretched out Short n’ ...

This repository is a comprehensive guide to different Encoding techniques in Machine Learning, explaining when to use each method and best practices. You'll find practical examples, ready-to-use code, ...