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Zeitschrift für Formulierungswissenschaft und Bioverfügbarkeit

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Betaine Solutions′ Interfacial Dilational Rheology: Anionic Surfactant and Polymer Effects

Abstract

CNNs, Machine learning, Reinforcement learning, Healthcare

Machine learning has emerged as a powerful tool in various industries, revolutionizing the way we analyze data and make predictions. Over the past few years, significant advancements have been made in machine learning techniques, algorithms, and applications. This article provides a comprehensive review of recent developments in machine-learning-based technologies, highlighting the key advancements and their impact on various domains. Deep learning has been at the forefront of machine learning research, enabling the development of sophisticated neural networks capable of solving complex problems. Recent developments in deep learning have focused on improving model architectures, training algorithms, and computational efficiency. Notably, advancements in Convolutional Neural Networks (CNNs) have revolutionized computer vision tasks, such as image classification, object detection, and image generation. The introduction of architectures like ResNet, Inception, and Transformer models has significantly improved accuracy and efficiency in these areas.

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