503 results for machine learning
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Hyperparameter Tuning for Machine and Deep Learning with R
…in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The…
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Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches
…methods for detecting and mapping alien plants: photointerpretation, machine learning classification, and field monitoring. Yucca gloriosa L., an invasive species in Regional Park of Migliarino-San Rossore-Massaciuccoli (Tuscany, Italy), served as the target species. Using RGB DJI Phantom 4 Pro v…
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Chapter Vision Goes Symbolic Without Loss of Information Within the Preattentive Vision Phase: The Need to Shift the Learning Paradigm from Machine-Learning (from Examples) to Machine-Teaching (by Rules) at the First Stage of a Two-Stage Hybrid Remote... Part I
Life sciences: general issues
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Book Chapter Full text
Chapter Vision Goes Symbolic Without Loss of Information Within the Preattentive Vision Phase: The Need to Shift the Learning Paradigm from Machine-Learning (from Examples) to Machine-Teaching (by Rules) at the First Stage of a Two-Stage Hybrid Remote... Part II
Optical physics
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Machine translation for everyone
Language learning and translation have always been complementary pillars of multilingualism in the European Union. Both have been affected by the increasing availability of machine translation (MT): language learners now make use of free online MT to help them both understand and produce texts in a…
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Deep Learning Applications
Deep learning is a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. This book is divided into two sections. The first section covers deep learning…
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Book Full text
Learning to Quantify
This open access book provides an introduction and an overview of learning to quantify (a.k.a. “quantification”), i.e. the task of training estimators of class proportions in unlabeled data by means of supervised learning. In data science, learning to quantify is a task of its own related to…
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Chapter 6 Learning to Discriminate
…recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the resulting predictive model does not use race as an explicit…
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Chapter TransRecipe for Translating Recipes through Machine Processing
This book details the process of building a Chinese-English machine translation system that automatically translates Chinese recipes into English through machine processing without human intervention ( TransRecipe ). This system is able to translate recipes into pictures and videos ( VisualRecipe )…
Also available at: OAPEN
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Advanced Learning Analytics Methods
This is an open access book. This comprehensive and timely methodological book introduces several novel topics under the overarching sections of advanced learning analytics (LA), artificial intelligence (AI), precision education, and complex systems. These topics are presented using accessible…
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Chapter Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge
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Learning Analytics Methods and Tutorials
This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the…
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Representation Learning for Natural Language Processing
This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning…
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Book Full text
Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including…
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AI in Learning: Designing the Future
AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into…
Also available at: OAPEN
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Chapter Risk Assessment and Automated Anomaly Detection Using a Deep Learning Architecture
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Also available at: OAPEN
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Book Full text
Handbook of Personalized Learning
The Handbook of Personalized Learning offers a theoretically grounded conceptualization for the development and implementation of personalizing learning. This comprehensive volume addresses personalized learning’s roots in educational, cognitive, and social psychological studies of learning as well…