What Every Engineer Should Know About Data Driven Analytics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download What Every Engineer Should Know About Data Driven Analytics PDF full book. Access full book title What Every Engineer Should Know About Data Driven Analytics.
Author | : Satish Mahadevan Srinivasan |
Publisher | : CRC Press |
Total Pages | : 250 |
Release | : 2023-04-13 |
Genre | : Computers |
ISBN | : 100085972X |
Download What Every Engineer Should Know About Data-Driven Analytics Book in PDF, ePub and Kindle
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.
Author | : Satish Mahadevan Srinivasan |
Publisher | : CRC Press |
Total Pages | : 279 |
Release | : 2023-04-13 |
Genre | : Computers |
ISBN | : 100085969X |
Download What Every Engineer Should Know About Data-Driven Analytics Book in PDF, ePub and Kindle
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.
Author | : Sarah Horton |
Publisher | : CRC Press |
Total Pages | : 258 |
Release | : 2024-04-30 |
Genre | : Business & Economics |
ISBN | : 1040009832 |
Download What Every Engineer Should Know About Digital Accessibility Book in PDF, ePub and Kindle
Accessibility is a core quality of digital products to be deliberately addressed throughout the development lifecycle. What Every Engineer Should Know About Digital Accessibility will prepare readers to integrate digital accessibility into their engineering practices. Readers will learn how to accurately frame accessibility as an engineering challenge so they are able to address the correct problems in the correct way. Illustrated with diverse perspectives from accessibility practitioners and advocates, this book describes how people with disabilities use technology, the nature of accessibility barriers in the digital world, and the role of engineers in breaking down those barriers. Accessibility competence for current, emerging, and future technologies is addressed through a combination of guiding principles, core attributes and requirements, and accessibility‐informed engineering practices. FEATURES Discusses how technology can support inclusion for people with disabilities and how rigorous engineering processes help create quality user experiences without introducing accessibility barriers Explains foundational principles and guidelines that build core competency in digital accessibility as they are applied across diverse and emerging technology platforms Highlights practical insights into how engineering teams can effectively address accessibility throughout the technology development lifecycle Uses international standards to define and measure accessibility quality Written to be accessible to non‐experts in the subject area, What Every Engineer Should Know About Digital Accessibility is aimed at students, professionals, and researchers in the field of software engineering.
Author | : Valdemar Vicente Graciano Neto |
Publisher | : CRC Press |
Total Pages | : 289 |
Release | : 2023-10-03 |
Genre | : Technology & Engineering |
ISBN | : 1000959163 |
Download What Every Engineer Should Know About Smart Cities Book in PDF, ePub and Kindle
Get ready to be at the forefront of the future of urban development! As cities continue to rapidly grow, the demand for sustainable and efficient infrastructure becomes more urgent. That’s where What Every Engineer Should Know About Smart Cities comes in, offering a comprehensive guide to the concepts and technologies driving the transformation of our cities. Delve into the world of smart cities and discover how information and communication technologies are revolutionizing urban environments. With clear definitions and a focus on real-world applications, this book explores the benefits and challenges of smart cities. It also highlights interdisciplinary topics such as smart buildings, autonomous cars, and urban emergency management systems. This book is not just a theoretical exploration of smart cities. It goes beyond that by providing an in-depth look at the key technologies that are essential to creating smart cities. From the Internet of Things and blockchain to digital twins and modeling and simulations, readers will gain a solid understanding of the foundational technologies that make smart cities possible. With detailed discussions and real-world examples of smart mobility, smart health, smart education, and smart agribusiness, readers will gain a deep understanding of the requirements and characteristics that engineers need to contribute to the development of smart cities. Whether you’re an engineer looking to expand your knowledge, a city planner seeking to understand the latest trends, or simply someone interested in the future of urban living, What Every Engineer Should Know About Smart Cities is the ultimate guide to unlocking the potential of smart cities for sustainable urban development and improved quality of life.
Author | : Mohammad Modarres |
Publisher | : CRC Press |
Total Pages | : 481 |
Release | : 2023-04-26 |
Genre | : Technology & Engineering |
ISBN | : 1000864103 |
Download Reliability and Risk Analysis Book in PDF, ePub and Kindle
Emphasises an introduction and explanation of the practical methods used in reliability, and risk studies with a discussion of their uses and limitations Offers basic and advanced methods in reliability analysis that are commonly used in daily practice Provides methods that address unique topics such as dependent failure analysis, importance analysis, and analysis of repairable systems Presents a comprehensive overview of modern probabilistic life assessment methods such as Bayesian estimation, system reliability analysis, and human reliability Includes many ends of chapter problems, a tools website with computational codes, along with a solutions manual to support course adoptions
Author | : Carl Anderson |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 300 |
Release | : 2015-07-23 |
Genre | : Business & Economics |
ISBN | : 1491916885 |
Download Creating a Data-Driven Organization Book in PDF, ePub and Kindle
"What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company ... Through interviews and examples from data scientists and analytics leaders in a variety of industries ... Anderson explains the analytics value chain you need to adopt when building predictive business models"--Publisher's description.
Author | : Piyanka Jain |
Publisher | : AMACOM |
Total Pages | : 276 |
Release | : 2014-11-05 |
Genre | : Business & Economics |
ISBN | : 0814449220 |
Download Behind Every Good Decision Book in PDF, ePub and Kindle
There is a misconception in business that the only data that matters is BIG data, and that elaborate tools and data scientists are required to extract any practical information. However, nothing could be further from the truth. If you feel that you can’t understand how to read, let alone implement, these complex software programs that crunch the data and spit out more data, that will no longer be a problem! Authors and analytics experts Piyanka Jain and Puneet Sharma demystify the process of business analytics and demonstrate how professionals at any level can take the information at their disposal and in only five simple steps--using only Excel as a tool--make the decision necessary to increase revenue, decrease costs, improve product, or whatever else is being asked of them at that time. In Behind Every Good Decision, you will learn how to: Clarify the business question Lay out a hypothesis-driven plan Pull relevant data Convert it to insights Make decisions that make an impact Packed with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80 percent of all business problems. It doesn’t take a numbers person to know that is a formula you need!
Author | : Tobias Macey |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 243 |
Release | : 2021-06-11 |
Genre | : Computers |
ISBN | : 1492062367 |
Download 97 Things Every Data Engineer Should Know Book in PDF, ePub and Kindle
Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail
Author | : Russell Dawson |
Publisher | : Jws Publishing |
Total Pages | : 0 |
Release | : 2023-12-20 |
Genre | : Computers |
ISBN | : |
Download Fundamentals of Data Analytics Book in PDF, ePub and Kindle
Gain a competitive edge in today's data-driven world and build a rich career as a data professional that drives business success and innovation... Did you know that every minute, people around the world make 5.9 million searches on Google, share 1.7 million posts on Facebook, and watch 1 million hours of videos? And that's not even all of it! In total, the world creates a massive 328 million terabytes of data every day! Data is everywhere... and it has become the essential building block of this modern society, shaping the future of businesses, technology, and human interactions. It's no wonder that data professional roles, such as data analysts, data scientists, and data architects are now highly in demand in this data-driven world. And that's why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book has all the answers! Building a successful career in data is all about cultivating the necessary mindset, knowledge, and skills. This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems. Here is just a fraction of what you will discover: A comprehensive guide to the data analytics process - a beginner-friendly 5-step framework to kickstart your journey into analyzing and processing data How to get started with the fundamental concepts, theories, and models for accurately analyzing data Everything you ever needed to know about data mining and machine learning principles - your gateway to unlocking the secrets of data's hidden potential Why business run on a data-driven culture, and how you can leverage it using real-time business intelligence analytics Strategies and techniques to build a problem-solving mindset that can overcome any complex and unique dataset How to create compelling and dynamic visualizations that help generate insights and make data-driven decisions The 4 pillars of a new digital world - discover how emerging technologies will transform the landscape of analyzing data And much more. Believe it or not, you can be terrible in math or statistics and still pursue a career in data. Yes, you need a good grasp of the basics but always keep in mind that knowledge can be acquired and skills can be developed. The key is to not be intimidated by the strings of characters and numbers. Focus, instead, on building a mindset that thirsts for knowledge. You'll be surprised by how much you're able to do with just that. And this book is here to guide you throughout this journey, so that crunching data becomes second nature to you. So, what are you waiting for? Ready to master the fundamentals and build a successful career in data analytics?
Author | : Kukatlapalli Pradeep Kumar |
Publisher | : John Wiley & Sons |
Total Pages | : 367 |
Release | : 2023-08-29 |
Genre | : Mathematics |
ISBN | : 1119841976 |
Download Data Engineering and Data Science Book in PDF, ePub and Kindle
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.