Data Science For Business

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Data Science for Business

Foster Provost,Tom Fawcett
Data Science for Business Book PDF

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 506 pages
File Size : 48,6 Mb
Release : 2013-07-27
Category : Computers
ISBN : 9781449374280

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Data Science for Business by Foster Provost,Tom Fawcett Pdf

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Data Science for Business and Decision Making

Luiz Paulo Favero,Patricia Belfiore
Data Science for Business and Decision Making Book PDF

Author : Luiz Paulo Favero,Patricia Belfiore
Publisher : Academic Press
Page : 1246 pages
File Size : 51,8 Mb
Release : 2019-04-11
Category : Business & Economics
ISBN : 9780128112175

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Data Science for Business and Decision Making by Luiz Paulo Favero,Patricia Belfiore Pdf

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. - Combines statistics and operations research modeling to teach the principles of business analytics - Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business - Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Matt Taddy
Business Data Science Combining Machine Learning and Economics to Optimize Automate and Accelerate Business Decisions Book PDF

Author : Matt Taddy
Publisher : McGraw Hill Professional
Page : 384 pages
File Size : 47,8 Mb
Release : 2019-08-23
Category : Business & Economics
ISBN : 9781260452785

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Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions by Matt Taddy Pdf

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: •Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling•Understand how use ML tools in real world business problems, where causation matters more that correlation•Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.

Data Science for Business With R

Jeffrey S. Saltz,Jeffrey M. Stanton
Data Science for Business With R Book PDF

Author : Jeffrey S. Saltz,Jeffrey M. Stanton
Publisher : SAGE Publications
Page : 485 pages
File Size : 45,6 Mb
Release : 2021-02-14
Category : Business & Economics
ISBN : 9781544370460

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Data Science for Business With R by Jeffrey S. Saltz,Jeffrey M. Stanton Pdf

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.

Data Science For Dummies

Lillian Pierson
Data Science For Dummies Book PDF

Author : Lillian Pierson
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 41,5 Mb
Release : 2021-08-20
Category : Computers
ISBN : 9781119811619

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Data Science For Dummies by Lillian Pierson Pdf

Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.

Data Science and Digital Business

Fausto Pedro García Márquez,Benjamin Lev
Data Science and Digital Business Book PDF

Author : Fausto Pedro García Márquez,Benjamin Lev
Publisher : Springer
Page : 319 pages
File Size : 48,5 Mb
Release : 2019-01-04
Category : Business & Economics
ISBN : 9783319956510

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Data Science and Digital Business by Fausto Pedro García Márquez,Benjamin Lev Pdf

This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

Data Science for Business Professionals

Probyto Data Science and Consulting Pvt. Ltd.
Data Science for Business Professionals Book PDF

Author : Probyto Data Science and Consulting Pvt. Ltd.
Publisher : BPB Publications
Page : 368 pages
File Size : 45,5 Mb
Release : 2020-05-06
Category : Computers
ISBN : 9789389423280

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Data Science for Business Professionals by Probyto Data Science and Consulting Pvt. Ltd. Pdf

Primer into the multidisciplinary world of Data Science KEY FEATURESÊÊ - Explore and use the key concepts of Statistics required to solve data science problems - Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app - Learn how to build Data Science solutions with GCP and AWS DESCRIPTIONÊ The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.Ê WHAT WILL YOU LEARNÊÊ - Understand the multi-disciplinary nature of Data Science - Get familiar with the key concepts in Mathematics and Statistics - Explore a few key ML algorithms and their use cases - Learn how to implement the basics of Data Pipelines - Get an overview of Cloud Computing & DevOps - Learn how to create visualizations using Tableau WHO THIS BOOK IS FORÊ This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science.Ê TABLE OF CONTENTS 1. Data Science in Practice 2. Mathematics Essentials 3. Statistics Essentials 4. Exploratory Data Analysis 5. Data preprocessing 6. Feature Engineering 7. Machine learning algorithms 8. Productionizing ML models 9. Data Flows in Enterprises 10. Introduction to Databases 11. Introduction to Big Data 12. DevOps for Data Science 13. Introduction to Cloud Computing 14. Deploy Model to Cloud 15. Introduction to Business IntelligenceÊ 16. Data Visualization Tools 17. Industry Use Case 1 Ð FormAssist 18. Industry Use Case 2 Ð PeopleReporter 19. Data Science Learning Resources 20. Do It Your Self Challenges 21. MCQs for Assessments

Recent Developments in Data Science and Business Analytics

Madjid Tavana,Srikanta Patnaik
Recent Developments in Data Science and Business Analytics Book PDF

Author : Madjid Tavana,Srikanta Patnaik
Publisher : Springer
Page : 494 pages
File Size : 40,8 Mb
Release : 2018-03-27
Category : Business & Economics
ISBN : 9783319727455

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Recent Developments in Data Science and Business Analytics by Madjid Tavana,Srikanta Patnaik Pdf

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

Data Science

Field Cady
Data Science Book PDF

Author : Field Cady
Publisher : John Wiley & Sons
Page : 208 pages
File Size : 51,5 Mb
Release : 2020-12-30
Category : Business & Economics
ISBN : 9781119544081

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Data Science by Field Cady Pdf

Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.

Data Science for Business

Foster Provost,Tom Fawcett
Data Science for Business Book PDF

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 50,9 Mb
Release : 2013-07-27
Category : Business & Economics
ISBN : 9781449374297

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Data Science for Business by Foster Provost,Tom Fawcett Pdf

Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, you will understand the many data-mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques.

Data Smart

John W. Foreman
Data Smart Book PDF

Author : John W. Foreman
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 44,8 Mb
Release : 2013-10-31
Category : Business & Economics
ISBN : 9781118839867

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Data Smart by John W. Foreman Pdf

Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Data Analysis for Business, Economics, and Policy

Gábor Békés,Gábor Kézdi
Data Analysis for Business Economics and Policy Book PDF

Author : Gábor Békés,Gábor Kézdi
Publisher : Cambridge University Press
Page : 741 pages
File Size : 41,7 Mb
Release : 2021-05-06
Category : Business & Economics
ISBN : 9781108483018

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Data Analysis for Business, Economics, and Policy by Gábor Békés,Gábor Kézdi Pdf

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Data Science for Economics and Finance

Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Data Science for Economics and Finance Book PDF

Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 41,8 Mb
Release : 2021
Category : Application software
ISBN : 9783030668914

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Data Science for Economics and Finance by Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana Pdf

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Machine Learning in Business

JOHN. HULL C,John Hull
Machine Learning in Business Book PDF

Author : JOHN. HULL C,John Hull
Publisher : Unknown
Page : 0 pages
File Size : 51,6 Mb
Release : 2021
Category : Big data
ISBN : 9798508489441

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Machine Learning in Business by JOHN. HULL C,John Hull Pdf

"The big data revolution is changing the way businesses operate and the skills required by managers. In creating the third edition, John Hull has continued to improve his material and added many new examples. The book explains the most popular machine learning algorithms clearly and succinctly; provides many examples of applications of machine learning in business; provides the knowledge managers need to work productively with data science professionals; has an accompanying website with data, worksheets, and Python code"--Back of cover.

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Chkoniya, Valentina
Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Book PDF

Author : Chkoniya, Valentina
Publisher : IGI Global
Page : 653 pages
File Size : 45,5 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781799869863

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Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry by Chkoniya, Valentina Pdf

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.