Weitere Bücher, die Sie mögen werden

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  Welcome to the Metaverse -...

  David L. Shrier

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  The metaverse. That term elicits a wide range of ideas and opinions. For many, it represents the next evolutionary phase of the internet—a fully immersive, digital universe where people can interact, work, and play in virtual environments. For others, it's yet another overhyped technology. So what is it, exactly? And what will its impact be? 
   
   
   
  While speculation and predictions about the metaverse are varied, one thing is clear: it is impacting the world of business as well as people's lives, and it will continue to do so in the future. The global metaverse market is predicted to be worth about $1 trillion by 2030, with over two billion users participating in some form of immersive experience. 
   
   
   
  There's a reason why companies are investing heavily in spatial computing and why platforms like Roblox are thriving. The metaverse, along with the technologies that underpin it, is still evolving, but it will eventually offer more ways for people to experience the world and each other. 
   
   
   
  In Welcome to the Metaverse, David Shrier, a world-leading futurist and the author of Welcome to AI, offers an entertaining look at the potential uses and impacts of this virtual space on business and life.

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  The Physics of Everyday Things -...

  Mark Hedges

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  Motion is a fundamental aspect of the physical world, affecting everything we do and experience. From walking down the street to driving a car, the principles of motion are always at work. In physics, understanding the forces that cause and influence motion is essential to understanding how objects behave in the world around us. This chapter will explore Newton's laws of motion and the application of forces in our daily lives, helping to make sense of the movements and actions that shape our experiences. 
  At the heart of motion is Newton's First Law, also known as the Law of Inertia. This law states that an object will remain at rest or in uniform motion unless acted upon by an external force. Essentially, things like to keep doing what they’re doing. For instance, a car coasting down the highway will continue moving unless the brakes are applied, or friction slows it down. This simple concept explains why, when you're in a car that suddenly stops, you feel as if you're still moving forward—your body wants to keep going, even though the car has halted. The application of this principle is not limited to vehicles but can be observed in everyday activities, like pushing a shopping cart or standing still on a bus that starts to move. 
  Newton's Second Law, the Law of Acceleration, takes it further. It tells us that the force applied to an object is equal to its mass times its acceleration (F = ma). This means that heavier objects require more force to accelerate, while lighter objects can be moved more easily. When you push a sled across the snow, the amount of effort you need depends on how much the sled weighs and how fast you want it to move. This relationship helps explain why it’s harder to get a heavy truck moving than a small bicycle. Understanding this law helps us calculate everything from how much effort it takes to lift an object to how quickly a rocket can launch into space.

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  Python Machine Learning for...

  Alexa Campbell

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  Have you thought about a career in data science? It's where the money is right now, and it's only going to become more widespread as the world evolves. Machine learning is a big part of data science, and for those that already have experience in programming, it's the next logical step. 
  Machine learning is a subsection of AI, or Artificial Intelligence, and computer science, using data and algorithms to imitate human thinking and learning. Through constant learning, machine learning gradually improves its accuracy, eventually providing the optimal results for the problem it has been assigned to. 
  It is one of the most important parts of data science and, as big data continues to expand, so too will the need for machine learning and AI. 
  Here's what you will learn in this quick guide to machine learning with Python for beginners:What machine learning isWhy Python is the best computer programming language for machine learningThe different types of machine learningHow linear regression worksThe different types of classificationHow to use SVMs (Support Vector Machines) with Scikit-LearnHow Decision Trees work with ClassificationHow K-Nearest Neighbors worksHow to find patterns in data with unsupervised learning algorithms 
  You will also find plenty of code examples to help you understand how everything works. 
  If you are ready to take your programming further, scroll up, click Buy Now, and find out why machine learning is the next logical step.

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  Data Analysis - Data Quality...

  Bright Mills

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  Data Analysis is a critical process in both academic and professional environments that involves inspecting, cleansing, transforming, and modeling data to discover useful information, derive conclusions, and support decision-making. It is foundational to nearly every field, from business and healthcare to engineering and social sciences. The ultimate aim of data analysis is to extract actionable insights from raw data, turning numbers and records into knowledge that can guide strategies and policy. 
  This paper provides an in-depth exploration of data analysis, covering both theoretical underpinnings and practical applications. It begins by defining what data analysis is and discussing its historical evolution. It delves into different types of data (quantitative, qualitative, structured, unstructured) and explains the steps in the data analysis lifecycle: from data collection and preparation to interpretation and reporting. 
  The paper further categorizes types of data analysis (descriptive, diagnostic, predictive, and prescriptive) and explains key techniques used in each. Statistical methods, data visualization, machine learning, and data mining approaches are thoroughly examined. Tools such as Excel, Python, R, and SQL are discussed in the context of their suitability for various analysis tasks. 
  Ethical considerations, data quality challenges, and real-world applications in industries like healthcare, marketing, finance, and public policy are also addressed. Finally, the paper concludes by highlighting emerging trends in data analysis, such as automated analytics and AI-driven insights. 
  This document serves as a comprehensive guide for students, researchers, professionals, and anyone interested in the field of data analysis, equipping readers with both conceptual knowledge and practical strategies to approach complex data-driven problems.

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  Silence - The Psychology and the...

  Olga V. Lehmann

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  In Silence: The Psychology and the Craft for Emotional Wellbeing, the author―a psychotherapist, university professor, educator, and researcher―takes the listener into a thought-provoking and heartfelt journey. She offers original perspectives and vulnerable stories from her clients, students, and personal life. Drawing on, among others, ethnographic and autoethnographic accounts, Lehmann serves the listener with psychological insights, offering a timely, critical, and thorough viewpoint to contrast with an overload of misinformation about what silence is and how people should feel when quiet. The listener will be challenged to aspire to balance when communicating or connecting with themselves, with others, with nature, or with art, or, for some, as part of a spiritual path. Whether in nature, at work meetings, on the road, in a classroom, in the therapy room, or at the dinner table, silences appear as coordinates, and this book is the missing map for surviving and thriving when navigating toward well-being.

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  Less Heat More Light - A Guided...

  John D. Aber

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  A straightforward and fact-based exploration of how weather happens, how it relates to climate, and how science answers major questions about Earth as a system 
   
   
    
  Climate change is one of the most hotly contested environmental topics of our day. To answer criticisms and synthesize available information, scientists have been driven to devise increasingly complex models of the climate system. This book conveys that the basics of climate and climate change have been known for decades, and that relatively simple descriptions can capture the major features of the climate system and help the general public understand what controls climate and weather, and how both might be changing. 
   
   
    
  Renowned environmental scientist and educator John D. Aber distills what he has learned from a long fascination with weather and climate, the process of science, and the telling of the story of science. This is not a book about policies and politics. Instead, it explores how weather happens, how it relates to climate, and how science has been used to answer major questions about the Earth as a system and inform policies that have reversed environmental degradation. By providing a guided tour of the science of weather, this thoughtful survey will contribute clarity and rationality to the public understanding of climate change.

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