In the era of big data and even bigger machine learning models, the environmental footprint of these technologies can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author Raghavendra Selvan exposes the high costs--both environmental and economic--of traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.
This essential read is for anyone in the machine learning field, from the academic researcher to the industry practitioner, who wants to make a meaningful impact on both their work and the world. This book enables readers to be agents of change toward a more sustainable and inclusive technological future. In this book, you will:
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Raghavendra Selvan (Raghav) is currently an Assistant Professor at the University of Copenhagen, with joint responsibilities at the Machine Learning Section (Dept. of Computer Science), Kiehn Lab (Department of Neuroscience) and the Data Science Laboratory. He received his PhD in Medical Image Analysis (University of Copenhagen, 2018). Raghavendra Selvan was born in Bangalore, India. His current research interests broadly pertain to Resource Efficient ML, Medical Image Analysis with ML, Quantum Tensor Networks and Graph Neural Networks. An overarching theme of his current research interests lies at the intersection of sustainability and ML where he is interested in investigating sustainability with ML, and also the sustainability of ML.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. In the era of big data and even bigger machine learning models, the environmental footprint of these technologies can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author Raghavendra Selvan exposes the high costs-both environmental and economic-of traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.This essential read is for anyone in the machine learning field, from the academic researcher to the industry practitioner, who wants to make a meaningful impact on both their work and the world. This book enables readers to be agents of change toward a more sustainable and inclusive technological future. In this book, you will:Learn strategies to significantly reduce the energy consumption, carbon footprint, and hardware demands of DL modelsExamine ways to break down barriers and foster a more inclusive future in AI developmentExplore strategies for cutting costs and minimizing ecological impactLearn how to balance performance with efficiency in model developmentGain proficiency in cutting-edge tools that enhance the sustainability of your AI projects. N° de réf. du vendeur LU-9781098155513
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Paperback. Etat : new. Paperback. In the era of big data and even bigger machine learning models, the environmental footprint of these technologies can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author Raghavendra Selvan exposes the high costs-both environmental and economic-of traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.This essential read is for anyone in the machine learning field, from the academic researcher to the industry practitioner, who wants to make a meaningful impact on both their work and the world. This book enables readers to be agents of change toward a more sustainable and inclusive technological future. In this book, you will:Learn strategies to significantly reduce the energy consumption, carbon footprint, and hardware demands of DL modelsExamine ways to break down barriers and foster a more inclusive future in AI developmentExplore strategies for cutting costs and minimizing ecological impactLearn how to balance performance with efficiency in model developmentGain proficiency in cutting-edge tools that enhance the sustainability of your AI projects Author Raghavendra Selvan exposes the high costs-both environmental and economic-traditional DL methods and presents practical solutions that pave the way for a more sustainable AI. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781098155513
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Paperback. Etat : New. In the era of big data and even bigger machine learning models, the environmental footprint of these technologies can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author Raghavendra Selvan exposes the high costs-both environmental and economic-of traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.This essential read is for anyone in the machine learning field, from the academic researcher to the industry practitioner, who wants to make a meaningful impact on both their work and the world. This book enables readers to be agents of change toward a more sustainable and inclusive technological future. In this book, you will:Learn strategies to significantly reduce the energy consumption, carbon footprint, and hardware demands of DL modelsExamine ways to break down barriers and foster a more inclusive future in AI developmentExplore strategies for cutting costs and minimizing ecological impactLearn how to balance performance with efficiency in model developmentGain proficiency in cutting-edge tools that enhance the sustainability of your AI projects. N° de réf. du vendeur LU-9781098155513
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