We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

The native just-in-time compiler in Python 3.15 can speed up code by as much as 20% or more, although it’s still experimental ...

Abstract: A machine-learning-assisted optimization (MLAO) method for antenna geometry design (AGD) (MLAO-AGD) is proposed. By combining machine learning (ML) methods, including a convolutional neural ...

Overview: Python supports every stage of data science from raw data to deployed systemsLibraries like NumPy and Pandas simplify data handling and analysisPython ...

Python has become the most popular language for using AI, and its creator believes that there’s an interesting reason why this is ...

Abstract: Spectral pixels are often a mixture of the pure spectra of the materials, called endmembers, due to the low spatial resolution of hyperspectral sensors, double scattering, and intimate ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

India has emerged as one of the world’s most dynamic and rapidly advancing centers for machine learning (ML)–enabled scientific research, according to the newly released <a href= ...