Applied Data Science And Machine Learning For Business Optimization 2025
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Applied Data Science And Machine Learning For Business Optimization 2025
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Author : Manish tripathi, Dr. Anshita Shukla
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Applied Data Science And Machine Learning For Business Optimization 2025 written by Manish tripathi, Dr. Anshita Shukla and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In today’s data-driven world, businesses are increasingly turning to data science and machine learning (ML) to gain a competitive edge, optimize operations, and make informed decisions. The ability to harness large volumes of data and apply advanced analytical techniques is transforming industries, enabling businesses to improve efficiency, reduce costs, and unlock new growth opportunities. As we enter an era where data is one of the most valuable assets, understanding how to apply data science and ML to real-world business problems is becoming an essential skill for professionals across all sectors. “Applied Data Science and Machine Learning for Business Optimization” aims to provide practical insights into how data science and ML can be utilized to optimize business functions and drive strategic decision-making. This book bridges the gap between theory and practice, offering actionable guidance on implementing advanced analytics and machine learning techniques to solve common business challenges. Whether you are a business analyst, data scientist, or decision-maker, this book equips you with the tools, techniques, and real-world examples needed to leverage data science for business success. The core focus of this book is on applying data science and ML to optimize critical areas of business, such as operations, marketing, customer experience, finance, and supply chain management. Each chapter walks through the methodologies used in data analysis, model building, and performance evaluation, providing a hands-on approach that empowers readers to apply these techniques to their own business contexts. From predictive analytics to recommendation systems, natural language processing, and optimization algorithms, the book covers a wide range of ML tools that are instrumental in solving real-world business problems. A major goal of this book is to showcase the power of data-driven decision-making. With the exponential growth of data and computing power, businesses now have unprecedented opportunities to analyze trends, predict future outcomes, and automate decision-making processes. However, it’s crucial to approach these opportunities with a clear understanding of how to integrate data science and ML into the organizational workflow, while ensuring alignment with business goals and strategies. We believe that the application of data science and ML should not be limited to advanced technologists alone. This book is written to demystify these technologies and make them accessible to business professionals, regardless of their technical background. By focusing on practical case studies, real-world examples, and step-by-step instructions, we hope to empower readers to implement data science and ML solutions that drive measurable business outcomes. Ultimately, the journey of business optimization through data science and machine learning is a continual process of learning, adapting, and evolving. As businesses begin to adopt and scale these technologies, they will unlock new capabilities, enhance operational efficiencies, and build a more agile, data-driven organization. “Applied Data Science and Machine Learning for Business Optimization” serves as a foundational resource to help navigate this transformative journey. We hope this book inspires you to harness the power of data science and machine learning in your own organization, unlocking innovative solutions and driving impactful changes in your business. Authors
Handbook Of Research On Applied Data Science And Artificial Intelligence In Business And Industry
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Author : Chkoniya, Valentina
language : en
Publisher: IGI Global
Release Date : 2021-06-25
Handbook Of Research On Applied Data Science And Artificial Intelligence In Business And Industry written by Chkoniya, Valentina and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
Artificial Intelligence For Business Optimization
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Author : Bhuvan Unhelkar
language : en
Publisher: CRC Press
Release Date : 2021-08-09
Artificial Intelligence For Business Optimization written by Bhuvan Unhelkar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-09 with Business & Economics categories.
This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.
Machine Learning And Data Science For Business Optimization A Practical Guide For Data Driven Decision Making
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Author : Sushira Somavarapu Om Goel
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-15
Machine Learning And Data Science For Business Optimization A Practical Guide For Data Driven Decision Making written by Sushira Somavarapu Om Goel and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-15 with Computers categories.
Machine Learning and Data Science for Business Optimization: A Practical Guide for Data-Driven Decision Making
Encyclopedia Of Data Science And Machine Learning
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2023-01-20
Encyclopedia Of Data Science And Machine Learning written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics
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Author : A. Ali
language : en
Publisher: Code Academy
Release Date : 2025-05-07
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics written by A. Ali and has been published by Code Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
Introducing Data Science for Beginners 2025 is your essential guide to understanding the fundamentals of data science, even if you have no prior experience. This beginner-friendly book breaks down core concepts such as data analysis, visualization, statistics, and the basics of machine learning. With real-world examples and simplified explanations, it helps you build a strong foundation in Python, data handling, and decision-making through data. Whether you're a student, professional, or enthusiast, this book provides the perfect starting point to enter the world of data science with confidence.
The Data Driven Product Manager A Blueprint 2025
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Author : Naga Srirama Narasimha Raviteja Malladi, Prof SumanYadav
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
The Data Driven Product Manager A Blueprint 2025 written by Naga Srirama Narasimha Raviteja Malladi, Prof SumanYadav and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In today’s rapidly evolving business landscape, the role of a product manager is more critical—and more complex—than ever before. “The Data-Driven Product Manager: A Blueprint” was born out of the recognition that intuition and experience, while valuable, can only take you so far. To truly excel in product management, one must harness the power of data to drive decision-making, fuel innovation, and ultimately deliver products that resonate with customers and succeed in the market. This book is designed as a comprehensive guide for product managers who are eager to integrate data-driven strategies into every facet of their work. Whether you are a seasoned professional looking to refine your approach or a newcomer seeking a structured path into the world of product management, this blueprint provides the tools, techniques, and insights necessary to transform raw data into actionable intelligence. Throughout the chapters, you will encounter practical frameworks and real-world examples that illustrate how data can be seamlessly integrated into product lifecycle management. From initial market research and customer segmentation to product launch and post-launch analysis, each section is crafted to offer a step-by-step roadmap for developing and scaling products in a competitive market. One of the key themes of this book is the transformation of data from a mere byproduct of operations into a strategic asset. In doing so, it addresses common obstacles such as data quality issues, integration challenges, and the cultural shift required within organizations to embrace analytics as a core component of the product management process. We offer actionable advice on building data infrastructure, fostering cross-functional collaboration, and cultivating a mindset that values experimentation and continuous improvement. The decision to write this book was fueled by the growing recognition that data-driven product management is not just a trend but a fundamental shift in how products are conceptualized, built, and refined. In an era where customer expectations are constantly evolving and market conditions can change overnight, the ability to adapt quickly using insights derived from data is no longer optional—it is essential for survival and success. I invite you to embark on this journey with an open mind and a readiness to challenge conventional practices. As you progress through the chapters, my hope is that you will find not only practical strategies and technical guidance but also inspiration to innovate boldly and lead confidently. Let this blueprint serve as both a reference and a catalyst for your growth as a data-driven product manager, empowering you to make informed decisions that drive real impact. Welcome to the future of product management. Welcome to a world where data lights the way forward. Authors
Innovation And Creativity In Tourism Business And Social Sciences
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Author : Vicky Katsoni
language : en
Publisher: Springer Nature
Release Date : 2025-06-03
Innovation And Creativity In Tourism Business And Social Sciences written by Vicky Katsoni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Business & Economics categories.
This book is the first volume of the proceedings of the 11th International Conference of the International Association of Cultural and Digital Tourism (IACuDiT). Focusing on “Innovation and Creativity in Tourism, Business and Social Sciences,” the conference was held from September 3 to 5, 2024, in Naxos, Greece. The book showcases the latest research on tourism business, technology, and the social sciences and presents a critical academic discourse on ICT adoption in the social sciences, regional development; sustainability and tourism experience; smart and sustainable practices; innovations in museum interpretation and collections management; emerging and disruptive technologies; gaming, gamification and augmented reality, and other topical aspects in business and the social sciences. The book discusses these digital transformation processes from various standpoints, including its effect on the social sciences combined with specific forms of tourism. The impact of digitalization encourages the emergence of new digital products and services based on the principle of flexibility. The book focuses on the knowledge economy and the “smart destinations” concepts and highlights new modes of tourism management and development, while further chapters address emerging technologies, such as the Internet of Things, AI, big data, and robotics in a range of tourism practices.
Applied Machine Learning For Data Science Practitioners
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Author : Vidya Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-01
Applied Machine Learning For Data Science Practitioners written by Vidya Subramanian and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-01 with Mathematics categories.
A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Data Science For Cyber Security
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Author : Nicholas A Heard
language : en
Publisher: World Scientific
Release Date : 2018-09-26
Data Science For Cyber Security written by Nicholas A Heard and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 with Computers categories.
Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies.