Scientific Books

Sustainable Ai: Tools For Moving Towards Green Ai Raghavendra Selvan O'reilly Media

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,...

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...

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Description

Description

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 models
  • Examine ways to break down barriers and foster a more inclusive future in AI development
  • Explore strategies for cutting costs and minimizing ecological impact
  • Learn how to balance performance with efficiency in model development
  • Gain proficiency in cutting-edge tools that enhance the sustainability of your AI projects

Pages: 250, Dimensions: 17.8x17.8cm

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Specifications

Specifications

Publisher
O'Reilly Media
Type
Environmental Sciences, Computers - Informatics, Physical Sciences, Artificial Intelligence
Language
English
Subtitle
-
Cover
Soft
Number of Pages
288
Release Date
10/2025
Publication Date
2025
Dimensions
-
ISBN-13
9781098155513

Important information

Specifications are collected from official manufacturer websites. Please verify the specifications before proceeding with your final purchase. If you notice any problem you can report it here.

See all specifications

Description & Specifications

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 models
  • Examine ways to break down barriers and foster a more inclusive future in AI development
  • Explore strategies for cutting costs and minimizing ecological impact
  • Learn how to balance performance with efficiency in model development
  • Gain proficiency in cutting-edge tools that enhance the sustainability of your AI projects

Pages: 250, Dimensions: 17.8x17.8cm

Manufacturer

Publisher
O'Reilly Media
Type
Environmental Sciences, Computers - Informatics, Physical Sciences, Artificial Intelligence
Language
English
Subtitle
-
Cover
Soft
Number of Pages
288
Release Date
10/2025
Publication Date
2025
Dimensions
-
ISBN-13
9781098155513

Important information

Specifications are collected from official manufacturer websites. Please verify the specifications before proceeding with your final purchase. If you notice any problem you can report it here.

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