In Machine Learning, your model is only as good as the data you feed it. But here is the catch: Algorithms only understand numbers. If your dataset contains words like "City," "Size," or "Status," you ...

In the field of orthodontics, the degree of fusion of the midpalatal suture (MPS) is a crucial factor in determining the most appropriate maxillary expansion technique. This study analyzed 600 ...

This study investigates Distributed Denial-of-Service (DDoS) attack detection within smart home environments using both traditional machine learning and deep learning approaches. Real smart home ...

1 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 2 Department of Computer Science, Rutgers University, New Brunswick, USA. Language identification is a fundamental ...

Predictive modeling is becoming a built-in capability across SAP, improving how teams handle forecasting, pricing, and planning. Many SAP professionals, however, aren’t machine-learning specialists, ...

Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause economic ...

This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...

Pruning optimises machine learning models by removing redundant or unimportant components. Originally introduced by Yann LeCun, pruning helps prevent overfitting in models. It can be used as a ...

Categorical features play a significant role in data preprocessing for machine learning models. These features must be converted into numerical formats for effective analysis and model accuracy.