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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.17538991 |
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Table of Contents:
- <p dir="ltr">The book "Machine Learning for Environmental Sustainability," is designed to establish and explore the vital intersection between global ecological crises and advanced artificial intelligence.</p> <p dir="ltr">The book t begins by asserting that environmental sustainability is an urgent global imperative, detailing the systemic threats posed by climate change, pervasive pollution, rapid biodiversity loss, and unsustainable resource depletion. It emphasizes that these are not isolated problems but a deeper imbalance demanding a paradigm shift in thinking and action, as traditional methods are insufficient to address the scale and interconnectedness of these issues.</p> <p dir="ltr">The book then pivots to highlight the pivotal role of technology, specifically Machine Learning (ML), as the necessary transformative force. ML is defined as a data-driven approach that allows computers to learn complex patterns without explicit programming, making it an ideal engine for environmental good. The foundational concepts of ML—including datasets, features, algorithms, and models across supervised, unsupervised, and reinforcement learning paradigms—are introduced to lay the technical groundwork.</p> <p dir="ltr">Ultimately, the report's purpose is to demonstrate that ML's capabilities in enhanced accuracy, accelerated analysis, and powerful prediction are indispensable tools for effectively monitoring, understanding, and protecting our planet's complex and fragile ecosystems, positioning it as a key enabler for a more resilient and environmentally responsible future.</p> <p dir="ltr">I owe a deep debt of gratitude to TechScholastic Press, Bengaluru, for their unwavering dedication and the critical role they played in the publication of this work.</p> <p><strong><br><br></strong></p> <p dir="ltr"> Many Thanks,</p> <p dir="ltr">Moka Nanditha Varma</p> <p> </p>