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Enter the world of Internet of Things with the power of data science with this highly practical, engaging book About This Book Explore real-world use cases from the Internet of Things (IoT) domain using decision science with this easy-to-follow, practical book Learn to make smarter decisions on top of your IoT solutions so that your IoT is smart in a real sense This highly practical, example-rich guide fills the gap between your knowledge of data science and IoT Who This Book Is For If you have a basic programming experience with R and want to solve business use cases in IoT using decision science then this book is for you. Even if your're a non-technical manager anchoring IoT projects, you can skip the code and still benefit from the book. What You Will Learn Explore decision science with respect to IoT Get to know the end to end analytics stack – Descriptive + Inquisitive + Predictive + Prescriptive Solve problems in IoT connected assets and connected operations Design and solve real-life IoT business use cases using cutting edge machine learning techniques Synthesize and assimilate results to form the perfect story for a business Master the art of problem solving when IoT meets decision science using a variety of statistical and machine learning techniques along with hands on tasks in R In Detail With an increasing number of devices getting connected to the Internet, massive amounts of data are being generated that can be used for analysis. This book helps you to understand Internet of Things in depth and decision science, and solve business use cases. With IoT, the frequency and impact of the problem is huge. Addressing a problem with such a huge impact requires a very structured approach. The entire journey of addressing the problem by defining it, designing the solution, and executing it using decision science is articulated in this book through engaging and easy-to-understand business use cases. You will get a detailed understanding of IoT, decision science, and the art of solving a business problem in IoT through decision science. By the end of this book, you'll have an understanding of the complex aspects of decision making in IoT and will be able to take that knowledge with you onto whatever project calls for it Style and approach This scenario-based tutorial approaches the topic systematically, allowing you to build upon what you learned in previous chapters.

Welcome to the world of data analysis! In today's data-driven era, the ability to effectively analyze and derive insights from data has become a vital skill for individuals and organizations across various domains. This book aims to serve as your comprehensive guide to understanding and performing data analysis, from the fundamental concepts to the practical applications. Chapter 1 introduces you to the fascinating realm of data analysis. We delve into the importance of data analysis in decision-making processes and highlight its role in gaining valuable insights and making informed choices. Understanding the power of data analysis sets the foundation for your journey ahead. Chapter 2 focuses on data entry, a crucial step in the data analysis process. We explore different methods and techniques for entering data accurately, ensuring the reliability and integrity of your dataset. Effective data entry practices are essential for obtaining meaningful results. In Chapter 3, we explore the different types of data analysis. Whether it's exploratory, descriptive, diagnostic, predictive, or prescriptive analysis, you will gain an understanding of each type and when to employ them in various scenarios. This chapter equips you with the knowledge to choose the appropriate analysis technique for your specific needs. To lay the groundwork for your data analysis journey, Chapter 4 familiarizes you with the basic terminology commonly used in the field. From variables and observations to measures of central tendency and variability, this chapter ensures you have a solid grasp of the foundational concepts necessary for effective data analysis. Chapter 5 focuses on setting up your data analysis environment. We guide you through the process of installing the necessary software and configuring your data workspace. Creating an optimal environment is crucial for seamless and efficient data analysis. Data preprocessing takes center stage in Chapter 6. We delve into the essential steps of data cleaning, transformation, and handling missing values. By mastering these techniques, you will be able to prepare your data for analysis, ensuring its quality and usability. In Chapter 7, we explore the exciting world of data exploration and visualization. Understanding the distribution of data and identifying relationships between variables are key aspects of uncovering meaningful insights. We delve into creating various charts and graphs to visually represent data, aiding in its interpretation and analysis. Chapter 8 introduces you to statistical analysis techniques. Descriptive statistics help us summarize and describe data, while inferential statistics enable us to make inferences and draw conclusions about populations based on sample data. Additionally, hypothesis testing allows us to validate our assumptions and test specific predictions. Predictive analytics takes the spotlight in Chapter 9. We explore techniques such as linear and logistic regression, decision trees, and clustering algorithms. These techniques empower you to make predictions and forecasts based on historical data, providing valuable insights for decision-making. Chapter 10 is dedicated to machine learning, an exciting field within data analysis. We introduce the fundamentals of machine learning, including supervised and unsupervised learning algorithms. Understanding these concepts opens doors to more advanced data analysis techniques and applications. Ethics in data analysis takes center stage in Chapter 11. We delve into the critical considerations of privacy concerns, data bias, and fairness in data analysis. Ethical data practices are crucial to ensure the responsible and ethical use of data in analysis. Chapter 12 explores the wide-ranging applications of data analysis. We delve into the domains of business analytics, healthcare analytics, sports analytics, and social media analytics, highlighting how data analysis drives insights and informs decision-making in these fields. Finally, Chapter 13 serves as a conclusion and sets you on the path for further learning and development. We recap the key concepts covered in the book, provide tips for advancing your data analysis skills, and discuss future trends and innovations in the field. We hope this book serves as a valuable resource in your data analysis journey. Whether you are a student, professional, or data enthusiast, we believe that understanding and applying data analysis.

This book on Security Analysis and Portfolio Management is a comprehensive source of information and analysis for students and practitioners. The distinguishing feature of the book is the detailed coverage of the regulatory environment, which consists of the current and updated rules and regulations, tax-environment and the practice of investment in the securities market in India. The book has been written keeping in mind the potential investor and an average student. It addresses all their doubts and concerns and makes them informed about the money market. This well organised, lucidly written text covers various aspects of the portfolio management, ranging from analysis to revision and then performance evaluation of the portfolio. Also discusses in detail the securities market, derivatives and risk evaluation that helps in understanding the trading system better and making quality investment decisions. Besides explaining the theoretical concepts of portfolio management, the book provides a detailed analysis of the latest development in the securities trading. It is meant to be a ‘single window book’ covering the SAPM syllabus of almost all the Indian Universities and institutes conducting MBA/PGDM or MCom programmes. The book will be equally useful for the students of ICAI, ICWAI as well as for investment courses conducted by NSE. Key Features • Easy to understand by the readers even if they have not been exposed to higher mathematics.• Vast coverage of the SAPM topics.• Several worked-out problems in relevant chapters to aid and assist students and teacher alike.• Detailed discussion on Indian stock and share market in context to the country’s current scenario.

Explains how anyone who learns the power of vision, voice, vectors, and values in the lives of those around them can be an outstanding leader. The direct result of the author's experience in teaching leadership and conducting management training sessions for professional organizations, this book describes four fundamental ideas that explain how and why people are compelled to follow: Values, Vision, Vector, and Voice. Together, these concepts form the essence of leadership and inform the steps necessary to inspire others to follow. The accessible, easy-to-read chapters differentiate leadership from management, connect the views and choices of followers with the definition and essential tasks of leadership, and link the "Four Vs" to tried and true concepts in leadership theory while drawing contrasts to conventional management wisdom.

Enabling Strategic Decision-Making in Organizations through Dataplex breaks down the role of data in strategic decision making, examining the organizational benefits but also utilising real-world examples of limitations and challenges and how these can be overcome.

This book comprehensively presents all the necessary information health professionals need to become Certified Asthma Educators. Competent asthma educators must possess a number of skills: they must have appropriate and sound medical and pharmaceutical knowledge; be proficient and effective educators who can influence their patients’ behaviors for the better; and, finally, they need the administrative and organizational skills needed to set up and run efficient clinics at their places of work. The book is divided into three sections to meet those needs: Asthma: The Fundamentals; The Role of Education; and, The Effective Asthma Educator. The first section covers clinical knowledge of asthma, with chapters including lung structure and function, clinical presentation of asthma, and environmental issues in asthma management. The second section delves into the role of educating patients and teaches readers how to best do that with an integrated approach between physician, educator, and patient. The third section looks further into educating techniques with a view of the learning process, considerations for instruction locations, and the role the educator plays overall. The final chapter in the book presents example cases for readers to assess the knowledge they have learned throughout. This second edition serves as both textbook and study guide for certification as well as a long-term reference publication. It has been fully updated from the previous edition with the latest treatment guidelines, medications, and disease monitoring methods. This is an ideal guide for asthma educators, those seeking NAECB certification, and any health professional involved with individuals who have asthma.

Apply the newest brain research to enhance all students’ learning Educational neuroscience consultant David A. Sousa continues his tradition of translating new findings into effective classroom strategies and activities in this updated version of his bestselling text. This fifth edition integrates recent developments in neuroscience, education, and psychology and includes New information on memory systems, especially working memory capacity Updated research on how the explosion of technology is affecting the brain Current findings on brain organization and hemispheric specialization New evidence on how learning the arts enhances cognitive processing and creativity An expanded resources section More than 150 new or updated references