Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Hyperparameters tuning and features selection are two common steps in every machine learning pipeline. Most of the time they are computed separately and independently. This may result in suboptimal ...

Gradient-Free-Optimizers is a Python library for gradient-free optimization of black-box functions. It provides a unified interface to 23 optimization algorithms, from simple hill climbing to Bayesian ...

Institute of Translational Medicine at the Department of Health Sciences and Technology, ETH, Zurich 8093, Switzerland Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland ...

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for improving optimization techniques in machine learning! 💡🔧 #NesterovGradient ...

A cortical hierarchical architecture is vital for encoding and integrating sensorimotor-to-cognitive information. However, whether this gradient structure is disrupted in end-stage renal disease (ESRD ...

Abstract: Mangroves are one of the important blue carbon ecosystems that provide numerous benefits for humans and the surrounding environment. The mapping and monitoring of mangrove forests are ...

In the field of petroleum engineering and geophysics, accurately predicting pore pressure and fracture gradient is crucial for safe and efficient drilling operations. Python, with its powerful ...

ABSTRACT: This research introduces an innovative approach to image classification, by making use of Vision Transformer (ViT) architecture. In fact, Vision Transformers (ViT) have emerged as a ...