Enzymes with specific functions are becoming increasingly important in industry, medicine and environmental protection. For example, they make it possible to synthesize chemicals in a more ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
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Linear regression using gradient descent explained simply
Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
This repository explores the concept of Orthogonal Gradient Descent (OGD) as a method to mitigate catastrophic forgetting in deep neural networks during continual learning scenarios. Catastrophic ...
Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Guilin Medical University, Guilin, China Background: Liver metastasis is the most common site of metastasis in pancreatic ...
Abstract: It is desirable in many multi-objective machine learning applications, such as multi-task learning with conflicting objectives, multi-objective reinforcement learning, to find a Pareto ...
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