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Deep Learning Foundations and Concepts
This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning...
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A comparative analysis of deep learning and deep transfer learning approaches for identification of rice varieties
Rice is an essential staple food for human nutrition. Rice varieties worldwide have been planted, imported, and exported. During production and...
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Deep Learning Models A Practical Approach for Hands-On Professionals
This book focuses on and prioritizes a practical approach, minimizing theoretical concepts to deliver algorithms effectively. With deep learning...
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Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox
With the breakthrough of AlphaGo, deep reinforcement learning has become a recognized technique for solving sequential decision-making problems....
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Research trends in deep learning and machine learning for cloud computing security
Deep learning and machine learning show effectiveness in identifying and addressing cloud security threats. Despite the large number of articles...
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A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer’s disease
Alzheimer’s disease (AD) is a brain-related disease in which the condition of the patient gets worse with time. AD is not a curable disease by any...
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An enhanced deep learning method for multi-class brain tumor classification using deep transfer learning
Multi-class brain tumor classification is an important area of research in the field of medical imaging because of the different tumor...
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Deep Learning
Deep Learning orientiert sich am Modell des Gehirns. Das menschliche Gehirn besteht Schätzungen zufolge aus 86 Mrd. Nervenzellen und sehr vielen...
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Comparative Analysis of Machine Learning, Ensemble Learning and Deep Learning Classifiers for Parkinson’s Disease Detection
A progressive neurodegenerative ailment called Parkinson's disease (PD) is marked by the death of dopamine-producing cells in the substantia nigra...
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Deep Learning Overview
Among the various machine learning algorithms, deep learning has recently been dramatically used in different scopes. Deep learning models have been...
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Deep Learning
Deep learning comprises various other domains including machine learning, neural networks, artificial intelligence, etc. Neutral networks form a core...
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Diabetes detection based on machine learning and deep learning approaches
The increasing number of diabetes individuals in the globe has alarmed the medical sector to seek alternatives to improve their medical technologies....
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Topological deep learning: a review of an emerging paradigm
Topological deep learning (TDL) is an emerging area that combines the principles of Topological data analysis (TDA) with deep learning techniques....
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Deep doubly robust outcome weighted learning
Precision medicine is a framework that adapts treatment strategies to a patient’s individual characteristics and provides helpful clinical decision...
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Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
Chronic kidney disease (CKD) is one of today’s most serious illnesses. Because this disease usually does not manifest itself until the kidney is...
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Deep Learning
In this chapter, we introduce the main concepts of Neural Networks and Deep Learning. We review the mathematical foundations and implement the...
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CNN-Transformer: A deep learning method for automatically identifying learning engagement
Learning engagement is an essential indication to define students' learning pacification in the class, and its automated identification technique is...
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Machine Learning and Deep Learning Algorithms
This chapter provides a brief overview of how machine learning and deep learning algorithms are trained for biomedical natural language processing...
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Deep learning-based personalized learning recommendation system design for "T++" Guzheng Pedagogy
This study investigates the development and impact of a deep learning-based personalized learning recommendation system designed specifically for...
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Deep learning for named entity recognition: a survey
Named entity recognition (NER) aims to identify the required entities and their types from unstructured text, which can be utilized for the...
