Other books that might interest you

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  Cybersecurity and Privacy Law...

  ConvoCourses

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  LOCKIN your organization's COMPLIANCE! KNOW THE LAW 
  This is an introduction to the cybersecurity and privacy laws that you need to know. This indispensable resource is tailored for those who deal with IT and legal practice:Know what laws apply: Navigate the intricate web of US Cyber laws and critical international regulations with confidence.Industry-Specific Insights: Gain a keen understanding of legal implications across various sectors, from finance to government.Practical Integration: Learn how to seamlessly weave legal frameworks into your organization's information security strategies. 
   Narrated by Kim Pepper

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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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  Environmental Monitoring Systems...

  Ben Rizer

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  "Environmental Monitoring Systems: Innovative Approaches and Technologies for Sustainable Development and Environmental Protection" delves into the critical role of monitoring systems in safeguarding our planet's ecosystems. As environmental challenges intensify, understanding the tools and technologies available for effective monitoring has never been more vital. 
  This comprehensive guide explores a wide array of innovative approaches in environmental monitoring, covering topics such as air and water quality assessment, soil health evaluation, and biodiversity tracking. The book provides insights into the latest advancements in sensor technologies, data collection methods, and analytical tools, emphasizing the integration of Internet of Things (IoT) devices and remote sensing techniques. 
  Readers will discover real-world applications of these systems across various sectors, including urban planning, disaster management, wildlife conservation, and climate change mitigation. Through compelling case studies and expert perspectives, the book highlights successful initiatives that demonstrate the power of data-driven decision-making in promoting sustainability. 
  Moreover, the book addresses the challenges and limitations faced in the field of environmental monitoring, from technical hurdles to regulatory concerns. It emphasizes the importance of community engagement and collaboration, showcasing how citizen science and participatory monitoring initiatives can enhance data collection and foster a culture of environmental stewardship. 
  "Environmental Monitoring Systems" equips you with the knowledge and tools to understand and contribute to the future of our planet. Join us on this journey to explore how innovative monitoring systems can pave the way for a sustainable and resilient world. 
   

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  The Plague

  Santiago Machain

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  This audiobook is narrated by an AI Voice.   
  The Plague explores the profound changes and enduring continuities that shaped European society in the wake of the Black Death and other crises of the 1300s. Through a series of thematic chapters, the book examines the resilience of communities, the evolution of social and economic structures, the persistence of faith, and the seeds of cultural and intellectual transformation. Far from being an age of unmitigated darkness, the fourteenth century emerges as a dynamic period of adaptation, creativity, and the quiet beginnings of the modern world.

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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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  Data Cleaning and Preprocessing...

  Simon Winston

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  In the age of data-driven decision-making, the quality of your data is the foundation upon which all your insights and analyses are built. "Data Cleaning and Preprocessing: The Foundation of Data Analysis" is your essential guide to mastering the crucial yet often underestimated processes of cleaning and preparing data for meaningful analysis. 
  From data scientists and analysts to business professionals and researchers, anyone working with data can benefit from this comprehensive and accessible book. It demystifies the complex world of data cleaning and preprocessing, making it accessible to both beginners and experienced practitioners. 
  Discover the fundamental principles of data quality and learn how to identify and address common data issues, such as missing values, outliers, and inconsistent records. Dive into essential techniques for handling data imperfections, from data imputation to outlier detection, and explore the art of feature engineering and dimensionality reduction to enhance the predictive power of your data. 
  The book provides hands-on guidance for implementing data cleaning and preprocessing techniques using popular programming languages like Python, R, and SQL, with practical examples and code samples. You'll also gain insights into best practices, data quality assessment, and the latest trends in the field, including ethical considerations and the application of AI and machine learning to automate data cleaning. 
  "Data Cleaning and Preprocessing: The Foundation of Data Analysis" is the go-to resource for harnessing the true potential of your data. It's a must-read for anyone who understands that quality data is not a luxury but a necessity in the data-driven world we live in. Take control of your data, unlock its potential, and transform the way you approach data analysis with this indispensable guide. 
   

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