Products related to Algorithm:
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Data Analytics in Marketing, Entrepreneurship, and Innovation
Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences.Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics.It features case studies that provide realistic examples of applications.This multifaceted examination of data analytics looks at: Business analyticsApplying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analyticsDeveloping new productsTechnopreneurshipDisruptive versus incremental innovationThe book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing.Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery.Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques.Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.
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Data Analytics for Business : Lessons for Sales, Marketing, and Strategy
Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down.This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications.The foundation of this text is the author’s 20-plus years of developing and delivering big data and artificial intelligence solutions across multiple industries: financial services, pharmaceuticals, consumer packaged goods, media, and retail.He provides guidelines and summarized cases for those studying or working in the fields of data science, data engineering, and business analytics.The book also offers a distinctive style: a series of essays, each of which summarizes a critical lesson or provides a step-by-step business process, with specific examples of successes and failures. Sales and marketing executives, project managers, business and engineering professionals, and graduate students will find this clear and comprehensive book the ideal companion when navigating the complex world of big data analytics.
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Business Models : Innovation, Digital Transformation, and Analytics
Since the beginning of time, running a business has involved using logic by which the business operates.This logic is called the business model in management science, which increasingly is focusing on issues surrounding business models.Research trends related to business models include value creation, value chain operationalization, and social and ecological aspects, as well as innovation and digital transformation.Business Models: Innovation, Digital Transformation, and Analytics examines how innovation, digital transformation, and the composition of value affect the existence and development of business models.The book starts by addressing the conceptual development of business models and by discussing the essence of innovation in those models.Chapters in the book investigate how: Business models can analyze digital transformation scenarios Individual business model elements effect selected performance measures as well as how the elements are significant for the enterprise value composition The environment effects the profitability of the high-growth enterprise business models Employer branding business models are perceived by the generation Z workforce To implement responsible business models in the enterprise Cyber risk is captured in business models Decision algorithms are important to business analyticsThis book is a compendium of knowledge about the use of business models in the context of innovative activities, digital transformation, and value composition.It attempts to combine the theory and practice and offers a look at business models currently used in companies, especially high-growth enterprises, in various countries of the world and indicates the prospects for their development.
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The Ethical Algorithm : The Science of Socially Aware Algorithm Design
Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life.In evolving from static computer programs hand-coded by engineers to the products of machine learning, these technologies have made our lives more efficient, more entertaining, and, sometimes, better informed.At the same time, complex algorithms are increasingly crushing the basic rights of individual citizens.Allegedly anonymized datasets and statistical models routinely leak our most sensitive personal information; applications for everything from loans to college reflect racial and gender bias.Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services and navigation apps.Understanding and improving the science behind the algorithms that run our lives is quickly becoming one of the most pressing issues of this century.Traditional solutions, such as laws, regulations and watchdog groups, have proven woefully inadequate, at best.Derived from the cutting-edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.Weaving together the science behind algorithm design with stories of citizens, lawyers, scientists, and activists experiencing the trial-and-error of research in real-time, Michael Kearns and Aaron Roth present a strikingly original way forward, showing how we can begin to work together to protect people from the unintended impacts of algorithms--and, sometimes, protect the science that could save us from ourselves.
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Which algorithm is better for a navigation software, the brute-force algorithm or the Dijkstra algorithm?
The Dijkstra algorithm is better for a navigation software compared to the brute-force algorithm. The Dijkstra algorithm is specifically designed for finding the shortest path in a graph, making it well-suited for navigation purposes. It efficiently calculates the shortest path from a starting point to all other points in the graph, which is essential for navigation software. On the other hand, the brute-force algorithm is not optimized for finding the shortest path and can be inefficient for large graphs, making it less suitable for navigation software.
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What is better: Saleswoman for Marketing Communication or E-Commerce?
The answer to this question depends on individual preferences and strengths. A saleswoman for marketing communication may be better suited for someone who enjoys building relationships, networking, and effectively communicating the value of products or services to potential clients. On the other hand, e-commerce may be a better fit for someone who is tech-savvy, enjoys analyzing data, and is interested in the digital marketplace. Both roles offer unique opportunities for success and growth, so it ultimately comes down to personal interests and skills.
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What is an algorithm?
An algorithm is a step-by-step procedure or set of rules to be followed in problem-solving or decision-making. It is a finite sequence of well-defined, computer-implementable instructions typically used to solve a specific problem or perform a specific task. Algorithms are used in various fields such as computer science, mathematics, and engineering to automate processes and achieve desired outcomes efficiently. They are essential in programming and data analysis to manipulate and process data effectively.
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What is Instagram's algorithm?
Instagram's algorithm is a complex system that determines the order in which posts appear on a user's feed. It takes into account various factors such as the user's interests, interactions, and relationships with other users. The algorithm prioritizes content that it believes the user will find most engaging, based on their past behavior on the platform. This means that not all posts from accounts a user follows will show up in their feed, as the algorithm aims to show the most relevant and interesting content to each individual user.
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Love Algorithm
In Love Algorithm, a tender touch of lyric love fuses with theharshness of profit-driven motivations to sharpen ourappreciation of the digital age.Loss of an authentic self is neverfar away but neither is hope for the discovery of a new kind offellowship.As the scenes shift from London to Paris to Shanghai,the poems intensify the global connections that make love aconstant riddle for all mankind.
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Digital Innovation and Entrepreneurship
The digital economy encompasses more than half the world, and in today's business market, those with a technology background have an advantage.This textbook provides students who already have digital expertise with a solid foundation in business and entrepreneurship in order to launch and run a business.Using a logical, objective-based structure, the book guides students to a comprehensive and practical understanding of innovation and entrepreneurship.Chapters progress through the steps in creating a successful digital business: framing the business, promotion and sales, delivery and operations, value capture, growth and scalability, intellectual property and protection, and leadership and structure.Features include: learning objectives, introductions, conclusions, tables and figures, highlighted key terms, and analysis and design exercises in each chapter; a wide range of real-world examples; a rolling case study of a hypothetical digital business that models the concepts covered in each chapter; appendices of business terms, including those relating to product licensing, customer service agreements and customer delivery contracts; and key terms explained throughout.Supplementary online resources include a test bank, lecture slides and a teaching guide for instructors, and a business design template for student use.
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Reshaping Entrepreneurship Education With Strategy and Innovation
New small business owners are constantly pressured to play a major role in the economic growth of their respected nation.However, revitalizing how individuals think, research, teach, and implement performance strategies to improve the operations of these small businesses is critical to entrepreneurial success. Reshaping Entrepreneurship Education With Strategy and Innovation is an essential reference source that discusses strategies to overcome performance barriers as well as implementation of effective entrepreneurial processes based on a wide range of global issues.Featuring research on topics such as authentic leadership, business ethics, and social entrepreneurship, this book is ideally designed for entrepreneurs, business professionals, scholars, researchers, students, and practitioners seeking coverage on innovative performance operations of small businesses.
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Digital Analytics for Marketing
This second edition of Digital Analytics for Marketing provides students with a comprehensive overview of the tools needed to measure digital activity and implement best practices when using data to inform marketing strategy.It is the first text of its kind to introduce students to analytics platforms from a practical marketing perspective. Demonstrating how to integrate large amounts of data from web, digital, social, and search platforms, this helpful guide offers actionable insights into data analysis, explaining how to "connect the dots" and "humanize" information to make effective marketing decisions.The authors cover timely topics, such as social media, web analytics, marketing analytics challenges, and dashboards, helping students to make sense of business measurement challenges, extract insights, and take effective actions.The book’s experiential approach, combined with chapter objectives, summaries, and review questions, will engage readers, deepening their learning by helping them to think outside the box. Filled with engaging, interactive exercises and interesting insights from industry experts, this book will appeal to undergraduate and postgraduate students of digital marketing, online marketing, and analytics. Online support materials for this book include an instructor’s manual, test bank, and PowerPoint slides.
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What is the Gauss algorithm?
The Gauss algorithm, also known as Gaussian elimination, is a method used to solve systems of linear equations. It involves transforming the system of equations into an equivalent upper triangular form by using elementary row operations, such as adding a multiple of one equation to another or swapping two equations. Once the system is in upper triangular form, the solutions can be easily obtained by back substitution. This algorithm is widely used in various fields such as engineering, physics, and computer science for solving systems of linear equations.
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What is a colloquial algorithm?
A colloquial algorithm is a step-by-step procedure or set of rules that is described in everyday language, rather than in formal mathematical or technical terms. It is typically used to explain a process or problem-solving method in a more accessible and understandable way for non-experts. Colloquial algorithms are often used in educational settings or in informal discussions to break down complex concepts into simpler, more relatable terms.
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What is the Snapchat algorithm?
The Snapchat algorithm is a complex system that determines the content users see on their feed based on their interactions and preferences. It analyzes factors such as who users interact with the most, what type of content they engage with, and how often they use the app. The algorithm then tailors the content to each user's interests, making the user experience more personalized. This algorithm is constantly evolving to provide the most relevant and engaging content to users.
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What is the bubblesort algorithm?
The bubblesort algorithm is a simple sorting algorithm that repeatedly steps through the list to be sorted, compares each pair of adjacent items, and swaps them if they are in the wrong order. This process is repeated until the list is sorted. The algorithm gets its name because smaller elements "bubble" to the top of the list with each iteration. While bubblesort is easy to understand and implement, it is not very efficient for large lists as it has a time complexity of O(n^2).
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