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Paperback. Zustand: new. Paperback. Smart Cities and AI: How Artificial Intelligence is Transforming Urban Living is your ultimate guide to understanding how AI is reshaping the cities of the future. With urbanization on the rise, the need for smarter, more sustainable, and efficient cities is becoming increasingly important. This book explores how artificial intelligence (AI), the Internet of Things (IoT), and data analytics are converging to create smarter, more livable urban environments, revolutionizing everything from traffic management to energy usage.Through clear explanations, practical examples, and real-world case studies, you'll gain insights into how AI technologies are being applied to urban infrastructure, optimizing everything from transportation and waste management to healthcare, security, and beyond.Inside, you'll discover: Introduction to Smart Cities: Understand the concept of smart cities, how they integrate advanced technologies, and the role of AI in transforming urban environments into intelligent, responsive, and sustainable ecosystems.The Role of AI in City Infrastructure: Learn how AI is revolutionizing city infrastructure through predictive analytics, decision-making algorithms, and autonomous systems that optimize the use of resources and services.AI in Traffic and Transportation: Discover how AI is being used to improve urban mobility, including smart traffic management, autonomous vehicles, and intelligent public transportation systems that reduce congestion and improve efficiency.IoT and Smart Infrastructure: Explore how IoT devices and sensors embedded in the city's infrastructure help collect real-time data, and how AI analyzes this data to make predictions, optimize operations, and improve services.Data Analytics in Smart Cities: Learn how big data and advanced analytics are harnessed to make informed decisions about urban development, energy management, healthcare, and public safety. Understand the role of data-driven strategies in urban planning and sustainability.AI for Energy Efficiency: Discover how AI helps cities optimize energy consumption through smart grids, predictive maintenance, and AI-driven energy management systems that reduce waste and lower costs.Smart Healthcare in Urban Environments: Learn how AI-powered solutions in healthcare are improving diagnostics, patient care, and resource allocation in smart cities, making healthcare more accessible and efficient.Public Safety and AI-Driven Security: Explore how AI technologies like facial recognition, predictive policing, and smart surveillance systems are improving public safety, reducing crime rates, and making cities safer for residents.Waste Management and Sustainability: Understand how AI is optimizing waste collection, recycling processes, and environmental sustainability efforts through smart sensors, route optimization, and waste-to-energy technologies.Challenges and Ethical Considerations: Delve into the ethical and privacy issues surrounding the use of AI in smart cities, including data privacy, surveillance concerns, and ensuring equitable access to AI-driven services for all residents.The Future of Smart Cities: Look ahead to the future of smart cities, exploring upcoming innovations in AI, urban mobility, and sustainable living. Understand how AI will continue to shape the urban experience and contribute to creating more resilient, adaptive cities.By the end of this book, you'll have a thorough understanding of how AI is transforming the way cities operate, from improving efficiency to enhancing the quality of life for residents. You'll also have insights into the future of urban living and how AI can help create smarter, more sustai Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Zustand: new. Paperback. Python for Data Engineering: Build ETL Pipelines and Handle Big Data Efficiently with PythonUnlock the full potential of data engineering with "Python for Data Engineering", the essential guide for aspiring data engineers, data scientists, and IT professionals seeking to master the art of building robust ETL pipelines and managing big data using Python. Whether you're just beginning your data engineering journey or looking to enhance your existing skills, this comprehensive handbook provides the tools, techniques, and insights necessary to transform raw data into valuable assets for your organization.Dive into expertly structured chapters that blend theoretical knowledge with practical applications, covering everything from the fundamentals of data engineering and Python programming to advanced topics like distributed computing, real-time data processing, and cloud integration. Learn how to design, develop, and deploy scalable ETL pipelines that efficiently extract, transform, and load data from diverse sources. Discover best practices for handling large datasets, optimizing performance, and ensuring data quality and integrity throughout the data lifecycle."Python for Data Engineering" empowers you to: Master ETL Processes: Understand the core principles of ETL and learn how to implement efficient data extraction, transformation, and loading strategies using Python.Handle Big Data: Explore techniques for managing and processing large-scale datasets with tools like Apache Spark, Hadoop, and Dask, all within the Python ecosystem.Automate Workflows: Streamline data engineering tasks by automating repetitive processes with Python scripts and workflow management tools such as Airflow and Luigi.Design Scalable Pipelines: Build resilient and scalable data pipelines that can handle increasing data volumes and complexity with ease.Ensure Data Quality: Implement robust data validation, cleansing, and monitoring practices to maintain high-quality data standards.Leverage Cloud Services: Integrate Python-based data engineering solutions with leading cloud platforms like AWS, Google Cloud, and Azure for enhanced flexibility and scalability.Optimize Performance: Fine-tune your data engineering workflows for maximum efficiency, reducing latency and improving throughput.Implement Security Best Practices: Protect sensitive data by applying security measures and ensuring compliance with industry standards and regulations.Visualize and Report Data: Create insightful visualizations and reports to communicate data findings effectively using libraries like Matplotlib, Seaborn, and Plotly.Stay Ahead with Advanced Topics: Delve into cutting-edge technologies such as machine learning integration, real-time analytics, and serverless computing to keep your skills current and in demand.Packed with real-world examples, hands-on exercises, and expert tips, "Python for Data Engineering" serves as your indispensable companion in navigating the dynamic field of data engineering. Whether you're building data pipelines for business intelligence, supporting data-driven decision-making, or driving innovation through data analytics, this book equips you with the knowledge and skills to excel.Key Features: Comprehensive coverage of data engineering fundamentals and advanced Python techniquesStep-by-step tutorials for building and deploying ETL pipelinesIn-depth guides to handling and processing big data with Python-based toolsReal-world case studies illustrating best practices and common challengesPractical exercises and projects to reinforce learning and develop h Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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