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 English | 2021 | ISBN: 1138336181 | 297 pages | True PDF | 8.49 MB Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes  English | 2019 | ISBN: 1292244100 | 383 pages | True PDF | 20.12 MB Essentials of Marketing, seventh edition, provides an accessible, lively and engaging introduction to marketing. Taking a practical, tactical approach, the authors cover traditional marketing techniques and theories, as well as offering the most up to date critical perspectives. Using contemporary case studies, in-chapter examples and suggestions for further reading the book provides everything an undergraduate or CIM student needs to excel in their discipline. The 7th edition also includes increased content on digital marketing, as well as a new 'thinking ethically' feature which is designed to make students think about this vital area of marketing.  English | 2021 | ISBN: 0262542579 | 155 pages | True EPUB | 6.79 MB This innovative book offers a learn-by-doing guide to entrepreneurship that balances practical advice with rigorous academic content. It introduces important concepts, provides highly engaging examples, and supplies the tools needed to put lessons into practice, creating a research-supported, step-by-step reference for developing, testing, and pitching any startup idea. By integrating lean startup principles, design thinking, and elements of the jobs-to-be-done framework, this combination textbook-workbook allows readers to choose for themselves whether, or to what extent, to engage with theory. All of the book's ten chapters encourage hands-on effort, providing readers with easy-to-follow steps, calls to action, and attainable milestones. Aspiring entrepreneurs will find this systematic approach to be more efficient than haphazard trial and error, and much more likely to yield concrete results. Chapters begin with a "mini case," offering real-world examples of each step in the process. These cases―all featuring entrepreneurs working outside the Silicon Valley bubble―include a meadery operator that turned customers into advocates by designing compelling experiences and the development of a dating app for dog lovers that found a unique niche in a crowded market.  English | 2019 | ISBN: 1492041130 | 398 pages | True PDF | 9.97 MB To really learn data science, you should not only master the tools-data science libraries, frameworks, modules, and toolkits-but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data.  English | 2021 | ISBN: 0367628821 | 483 pages | True PDF | 54.07 MB Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud).Data Science and Data Analytics: Opportunities and Challengescovers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy.  English | 2021 | ISBN: 1492063495 | 254 pages | True PDF | 20.32 MB As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance requirements. Data governance incorporates the ways people, processes, and technology work together to ensure data is trustworthy and can be used effectively. This practical guide shows you how to effectively implement and scale data governance throughout your organization. Chief information, data, and security officers and their teams will learn strategy and tooling to support democratizing data and unlocking its value while enforcing security, privacy, and other governance standards. Through good data governance, you can inspire customer trust, enable your organization to identify business efficiencies, generate more competitive offerings, and improve customer experience. This book shows you how.  English | 2021 | ISBN: 1484272196 | 221 pages | pdf, epub | 5.62 MB Understand the process of setting up a successful cyber threat intelligence (CTI) practice within an established security team. This book shows you how threat information that has been collected, evaluated, and analyzed is a critical component in protecting your organization's resources. Adopting an intelligence-led approach enables your organization to nimbly react to situations as they develop. Security controls and responses can then be applied as soon as they become available, enabling prevention rather than response. There are a lot of competing approaches and ways of working, but this book cuts through the confusion. Author Aaron Roberts introduces the best practices and methods for using CTI successfully. This book will help not only senior security professionals, but also those looking to break into the industry. You will learn the theories and mindset needed to be successful in CTI. This book covers the cybersecurity wild west, the merits and limitations of structured intelligence data, and how using structured intelligence data can, and should, be the standard practice for any intelligence team. You will understand your organizations' risks, based on the industry and the adversaries you are most likely to face, the importance of open-source intelligence (OSINT) to any CTI practice, and discover the gaps that exist with your existing commercial solutions and where to plug those gaps, and much more.  English | 2019 | ISBN: 1492044199 | 372 pages | True PDF | 64.73 MB Despite popular forays into augmented and virtual reality in recent years, spatial computing still sits on the cusp of mainstream use. Developers, artists, and designers looking to enter this field today have few places to turn for expert guidance. In this book, Erin Pangilinan, Steve Lukas, and Vasanth Mohan examine the AR and VR development pipeline and provide hands-on practice to help you hone your skills. Through step-by-step tutorials, you'll learn how to build practical applications and experiences grounded in theory and backed by industry use cases. In each section of the book, industry specialists, including Timoni West, Victor Prisacariu, and Nicolas Meuleau, join the authors to explain the technology behind spatial computing.  English | 2021 | ISBN: 0367568500 | 299 pages | True PDF | 9.82 MB "A much-needed service for society today. I hope this book reaches information managers in the organization now vulnerable to hacks that are stealing corporate information and even holding it hostage for ransom." - Ronald W. Hull, author, poet, and former professor and university administrator  English | 2019 | ISBN: 1492036579 | 317 pages | True PDF | 11.23 MB If you're an executive, manager, or anyone interested in leveraging AI within your organization, this is your guide. You'll understand exactly what AI is, learn how to identify AI opportunities, and develop and execute a successful AI vision and strategy. Alex Castrounis, business consultant and former IndyCar engineer and race strategist, examines the value of AI and shows you how to develop an AI vision and strategy that benefits both people and business. AI is exciting, powerful, and game changing--but too many AI initiatives end in failure. With this book, you'll explore the risks, considerations, trade-offs, and constraints for pursuing an AI initiative. You'll learn how to create better human experiences and greater business success through winning AI solutions and human-centered products. |
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