Download or read book Creating Value with Data Analytics in Marketing written by Peter C. Verhoef and published by Routledge. This book was released on 2021-11-07 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key competing texts are practitioner-focused ‘how to’ guides, whilst our book combines rigorous theory with practical insight and examples, with authors from both the academic and business world, making it more adoptable as a student text; Unlike other books on the subject, this has a customer focus and an exploration of how big data can add value to customers as well as organisations; Enables readers to move from "big data" to "big solutions" by demonstrating how to integrate data analytics into specific goals and processes for implementation; Highly successful and well regarded both for students and practitioners

Download or read book Mastering Data Science and Big Data Analytics written by Maxine Chen and published by . This book was released on 2024-03-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on a transformative journey into the realm of data science and big data analytics with 'Mastering Data Science and Big Data Analytics: Strategies and Tools for Effective Analysis.' This comprehensive guide unveils essential techniques, strategies, and tools necessary to navigate the vast landscape of big data with confidence and proficiency. From foundational concepts to advanced methodologies, this book provides a holistic understanding of data science principles, empowering both aspiring data scientists and seasoned professionals alike to harness the power of data to drive informed decision-making and innovation. Through clear explanations and real-world examples, discover how to leverage cutting-edge tools and technologies to extract actionable insights from complex datasets. With a focus on practical application, 'Mastering Data Science and Big Data Analytics' equips you with the skills to tackle real-world challenges head-on, whether it's uncovering hidden patterns, predicting future trends, or optimizing business processes. Explore the latest advancements in machine learning, artificial intelligence, and data visualization, and gain proficiency in popular programming languages and frameworks such as Python, R, TensorFlow, and Apache Spark. Whether you're a data enthusiast looking to expand your skill set or a business leader striving to unlock the full potential of your data assets, this book serves as an indispensable companion on the journey to mastering data science and big data analytics. Empower yourself to turn data into actionable insights and drive meaningful impact in an increasingly data-driven world.

Download or read book Mastering Data Science and Big Data Analytics written by Nikhilesh Mishra and published by Independently Published. This book was released on 2023-08-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on an illuminating voyage through the captivating landscape of "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Application" From foundational principles to advanced methodologies, this comprehensive guide empowers you with the wisdom and expertise to navigate the intricate world of data science and big data analytics. Explore the fundamental concepts of data science, from data acquisition to predictive modeling. Dive deep into cutting-edge techniques, including exploratory data analysis and machine learning. Gain practical insights from real-world data analysis projects spanning diverse industries. Uncover the ethical considerations and societal implications of data-driven decision-making. Enhance your growth potential with an exclusive section dedicated to interviews and interviewers, providing valuable insights and skills that amplify your journey towards success. Whether you're a budding enthusiast or a seasoned practitioner, "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Applications" empowers you to elevate your expertise and become a visionary in the realm of data-driven innovation. Seize the opportunity-secure your copy today and embark on a transformative journey of knowledge and exploration!

Download or read book Mastering Python for Data Science written by Samir Madhavan and published by Packt Publishing Ltd. This book was released on 2015-08-31 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the world of data science through Python and learn how to make sense of data About This Book Master data science methods using Python and its libraries Create data visualizations and mine for patterns Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learning Who This Book Is For If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed. What You Will Learn Manage data and perform linear algebra in Python Derive inferences from the analysis by performing inferential statistics Solve data science problems in Python Create high-end visualizations using Python Evaluate and apply the linear regression technique to estimate the relationships among variables. Build recommendation engines with the various collaborative filtering algorithms Apply the ensemble methods to improve your predictions Work with big data technologies to handle data at scale In Detail Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving. This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science. Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods. Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics. Style and approach This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.

Download or read book Creating Value with Data Analytics in Marketing written by Peter C. Verhoef and published by Routledge. This book was released on 2021-11-07 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing. Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies. Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management. Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters.

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Download or read book Creating Value with Big Data Analytics written by Peter C. Verhoef and published by Routledge. This book was released on 2016-01-08 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

Download or read book Data Analytics written by Robert Keane and published by Createspace Independent Publishing Platform. This book was released on 2017-09-24 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics Master The Techniques For Data Science, Big Data And Data Analytics If your business is like most, it is already generating a staggering amount of data on a regular basis. Understanding what this data truly means is key to succeeding in the marketplace these days and if you are looking for a way to give yourself an edge then Data Analytics is the book you have been waiting for. Inside you will find the tools you need in order to take full advantage of all of the data that your business is already generating regardless if you are part of a major corporation or if you are a small business that is just starting out. There are currently over a quintillion byte of data being created each and every day and if you aren't considering how you can make the most of your share then you are already losing out to the competition. Inside this book you will find: Everything you need to know to get started completing the right kind of data analysis to benefit your business regardless of what that business is. The best ways to utilize predictive analysis effectively. Easy to use machine learning and regression techniques. The reasons why you need discrete choice models in your life. And more... So, what are you waiting for? Don't get left behind, do your business a favor and buy this book today! Scroll Up And Click The "BUY" Button!

Download or read book Mastering Spark for Data Science written by Andrew Morgan and published by Packt Publishing Ltd. This book was released on 2017-03-29 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to tell a compelling story with data science using Spark's ecosystem Explore data at scale and work with cutting edge data science methods Who This Book Is For This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes. What You Will Learn Learn the design patterns that integrate Spark into industrialized data science pipelines See how commercial data scientists design scalable code and reusable code for data science services Explore cutting edge data science methods so that you can study trends and causality Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs Find out how Spark can be used as a universal ingestion engine tool and as a web scraper Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams Study advanced Spark concepts, solution design patterns, and integration architectures Demonstrate powerful data science pipelines In Detail Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more. You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly. Style and approach This is an advanced guide for those with beginner-level familiarity with the Spark architecture and working with Data Science applications. Mastering Spark for Data Science is a practical tutorial that uses core Spark APIs and takes a deep dive into advanced libraries including: Spark SQL, visual streaming, and MLlib. This book expands on titles like: Machine Learning with Spark and Learning Spark. It is the next learning curve for those comfortable with Spark and looking to improve their skills.

Download or read book Python Data Science written by Computer Programming Academy and published by . This book was released on 2020-11-10 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inside this book you will find all the basic notions to start with Python and all the programming concepts to implement predictive analytics. With our proven strategies you will write efficient Python codes in less than a week!

Download or read book Big Data Analytics written by Kim H. Pries and published by CRC Press. This book was released on 2015-02-05 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Download or read book Mastering Marketing Data Science written by Iain Brown and published by John Wiley & Sons. This book was released on 2024-04-29 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Power of Data: Transform Your Marketing Strategies with Data Science In the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers, Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively. Comprehensive Coverage: From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science. Practical Applications: Engage with real-world examples, hands-on exercises in both Python & SAS, and actionable insights to apply in your marketing campaigns. Expert Guidance: Benefit from Dr. Iain Brown's decade of experience as he shares cutting-edge techniques and ethical considerations in marketing data science. Future-Ready Skills: Learn about the latest advancements, including generative AI, to stay ahead in the rapidly evolving marketing landscape. Accessible Learning: Tailored for both beginners and seasoned professionals, this book ensures a smooth learning curve with a clear, engaging narrative. Mastering Marketing Data Science is designed as a comprehensive how-to guide, weaving together theory and practice to offer a dynamic, workbook-style learning experience. Dr. Brown's voice and expertise guide you through the complexities of marketing data science, making sophisticated concepts accessible and actionable.

Download or read book Data Science written by Herbert Jones and published by Createspace Independent Publishing Platform. This book was released on 2018-11 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Did you know that the value of data usage has increased job opportunities, but that there are few specialists? These days, everyone is aware of the role that data can play, whether it is an election, business or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists. It combines analytical engineering, Machine Learning, Big Data, Data Mining, and Statistics in an easy to read and digest method. Data gathered from scientific measurements, customers, IoT sensors, and so on is very important only when one can draw meaning from it. Data Scientists are professionals that help disclose interesting and rewarding challenges of exploring, observing, analyzing, and interpreting data. To do that, they apply special techniques that help them discover the meaning of data. Becoming the best Data Scientist is more than just mastering analytic tools and techniques. The real deal lies in the way you apply your creative ability like expert Data Scientists. This book will help you discover that and get you there. The goal with Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't is to help you expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues. At the end of this book, you will learn how to combine Machine Learning, Data Mining, analytics, and programming, and extract real knowledge from data. As you read, you will discover important statistical techniques and algorithms that are helpful in learning Data Science. When you have finished, you will have a strong foundation to help you explore many other fields related to Data Science. This book will discuss the following topics: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Don't waste any time. Grab your copy today and learn quick tips from the best Data scientists!

Download or read book Mastering Java for Data Science written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. Style and approach This is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.

Download or read book Mastering Big Data Analytics written by Dr G Manimala and published by Notion Press. This book was released on 2024-08-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data analytics is the process of examining large volumes of data to uncover hidden patterns, correlations, and other useful information that can be used to make informed business decisions. It involves a complex interplay of technologies, tools, and human expertise. In today's data-driven world, organizations are inundated with vast amounts of information from diverse sources. The ability to harness this data and extract meaningful insights is no longer a luxury but a necessity for survival and growth. Big data analytics empowers businesses to make data-driven decisions, optimize operations, and gain a competitive edge. This book is your comprehensive guide to mastering the art and science of big data analytics. We delve into the core concepts, tools, techniques, and best practices that form the foundation of successful data-driven initiatives. Whether you're a seasoned data scientist, a business analyst seeking to expand your skill set, or a curious enthusiast, this book will equip you with the knowledge and skills to unlock the full potential of your data.

Download or read book Big Data Science Analytics written by Arshdeep Bahga and published by Vpt. This book was released on 2016-04-15 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. We have written this textbook to meet this need at colleges and universities, and also for big data service providers.

Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code