#1 NEW YORK TIMES BEST SELLER • In this urgent, authoritative book, Bill Gates sets out a wide-ranging, practical—and accessible—plan for how the world can get to zero greenhouse gas emissions in time to avoid a climate catastrophe. Bill Gates has spent a decade investigating the causes and effects of climate change. With the help of experts in the fields of physics, chemistry, biology, engineering, political science, and finance, he has focused on what must be done in order to stop the planet's slide to certain environmental disaster. In this book, he not only explains why we need to work toward net-zero emissions of greenhouse gases, but also details what we need to do to achieve this profoundly important goal. He gives us a clear-eyed description of the challenges we face. Drawing on his understanding of innovation and what it takes to get new ideas into the market, he describes the areas in which technology is already helping to reduce emissions, where and how the current technology can be made to function more effectively, where breakthrough technologies are needed, and who is working on these essential innovations. Finally, he lays out a concrete, practical plan for achieving the goal of zero emissions—suggesting not only policies that governments should adopt, but what we as individuals can do to keep our government, our employers, and ourselves accountable in this crucial enterprise. As Bill Gates makes clear, achieving zero emissions will not be simple or easy to do, but if we follow the plan he sets out here, it is a goal firmly within our reach.

Environmental Science for a Changing World captivates students with real-world stories while exploring the science concepts in context. Engaging stories plus vivid photos and infographics make the content relevant and visually enticing. The result is a text that emphasizes environmental, scientific, and information literacies in a way that engages students.

The main objective of these updated global guidelines is to offer health-based air quality guideline levels, expressed as long-term or short-term concentrations for six key air pollutants: PM2.5, PM10, ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. In addition, the guidelines provide interim targets to guide reduction efforts of these pollutants, as well as good practice statements for the management of certain types of PM (i.e., black carbon/elemental carbon, ultrafine particles, particles originating from sand and duststorms). These guidelines are not legally binding standards; however, they provide WHO Member States with an evidence-informed tool, which they can use to inform legislation and policy. Ultimately, the goal of these guidelines is to help reduce levels of air pollutants in order to decrease the enormous health burden resulting from the exposure to air pollution worldwide.

TAGLINE Deepfake Detection Unlocked: Python Approaches for Deepfake Images, Videos, Audio Detection. KEY FEATURES ● Comprehensive and graded approach to Deepfake detection using Python and its libraries. ● Practical implementation of deepfake detection techniques using Python. ● Hands-on chapters for detecting deepfake images, videos, and audio. ● Covers Case study for providing real-world application of deepfake detection. DESCRIPTION In today's digital world, mastering deepfake detection is crucial, with deepfake content increasing by 900% since 2019 and 96% used for malicious purposes like fraud and disinformation. "Ultimate Deepfake Detection with Python" equips you with the skills to combat this threat using Python’s AI libraries, offering practical tools to protect digital security across images, videos, and audio. This book explores generative AI and deepfakes, giving readers a clear understanding of how these technologies work and the challenges of detecting them. With practical Python code examples, it provides the tools necessary for effective deepfake detection across media types like images, videos, and audio. Each chapter covers vital topics, from setting up Python environments to using key datasets and advanced deep learning techniques. Perfect for researchers, developers, and cybersecurity professionals, this book enhances technical skills and deepens awareness of the ethical issues around deepfakes. Whether building new detection systems or improving current ones, this book offers expert strategies to stay ahead in digital media security. WHAT WILL YOU LEARN ● Understand the fundamentals of generative AI and deepfake technology and the potential risks they pose. ● Explore the various methods and techniques used to identify deepfakes, as well as the obstacles faced in this field. ● Learn to use essential datasets and label image, video, and audio data for building deepfake detection models. ● Apply advanced machine learning models like CNNs, RNNs, GANs, and Transformers for deepfake detection. ● Master active and passive methods for detecting face manipulation and build CNN-based image detection systems. ● Detect manipulations in videos, develop a detection system, and evaluate its performance using key metrics. ● Build and implement a practical deepfake detection system to understand how these techniques are applied in real-world scenarios. WHO IS THIS BOOK FOR? This book is tailored for anyone interested in deepfake detection using Python. Whether you're a researcher, developer, or cybersecurity professional, this guide provides the essential knowledge and skills. A basic understanding of Python and machine learning is helpful, but no prior experience in deepfakes is required. TABLE OF CONTENTS 1. Introduction to Generative AI and Deepfake Technology 2. Deepfake Detection Principles and Challenges 3. Ethical Considerations with the Use of Deepfakes 4. Setting Up your Machine for Deepfake Detection using Python 5. Deepfake Datasets 6. Techniques for Deepfake Detection 7. Detection of Deepfake Images 8. Detection of Deepfake Video 9. Detection of Deepfake Audio 10. Case Study in Deepfake Detection Index