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Author: Andrew Park Publisher: Andrew Park ISBN: 9781801779449 Category : Languages : en Pages : 0
Book Description
★ 55% OFF for Bookstores! NOW at $ 21,97 instead of $ 31.97! ★ Are you interested in knowing more about the fascinating world of Data Science? Your Customers Will Love This Amazing Step-By-Step Guide! This book offers you the fundamental knowledge you need to get started, but keep in mind that no book or even teacher can do everything for you. You need to work hard by putting each building block in its place as you advance. Data Science is a massive field of study that requires years of learning and practice before you can master it. This shouldn't discourage you, however! Embrace it as a challenge that you can undertake in order to broaden your horizons and improve your knowledge of all that is Data Science and machine learning. Data Science is a highly complex topic that has continuously been developed for decades. It is constantly evolving, and it can be challenging to keep up with all the past, present, and future concepts. With that being said, this isn't supposed to discourage you from pursuing this field. To start out this guidebook, we are going to take a look at what Data Science is all about, why it is important, and why we would want to work with this process in the first place as well. We will then take some time in order to learn the lifecycle of Data Science, and how we need to go through a series of steps like the finding the right data, preparing the data, coming up with the right model, and more. All of this and more will be discussed in this guidebook so that you can go from start to finish with your own Data Science project. This is just the start of some of the amazing things that we are able to do when it is time to start on Data Science. We are able to spend our time looking at what machine learning is all about, the different types of machine learning, and how we are able to put it all together to makes sure that we can create the right algorithms and models when it is time to sort through our data and find the right patterns and insights in the process. In "The Essential Guide on Data Science" you will discover: What is Data Science? Why is Data Science So Important? The Benefits of Python Data Science The Lifecycle of Data Science The Importance of Visuals with Data Science A Look at Data Mining The Real-Life Applications of Data Science There are a lot of benefits that we are able to see when it comes to working on Data Science, and many companies in a lot of different industries are going to work with this in order to ensure that we will be able to handle how to work with their customers, how to beat out the competition, and so much more. When you are ready to work with the idea of Data Science, and you want to work with all of the different parts that are found with it, then make sure to check out this guidebook to help you get started. You can position yourself to use your deep knowledge and understanding of all the cutting-edge technologies obtained from this book to contribute to the growth of any company and land yourself a new high paying and rewarding job! Buy It NOW and Let Your Customers Get Addicted to This Amazing Book!
Author: Bart Baesens Publisher: John Wiley & Sons ISBN: 1118892747 Category : Business & Economics Languages : en Pages : 256
Book Description
The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
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
Author: Przemek Chojecki Publisher: Przemek Chojecki ISBN: Category : Computers Languages : en Pages : 88
Book Description
We’re living in a digital world. Most of our global economy is digital and the sheer volume of data is stupendous. It’s 2020 and we’re living in the future. Data Scientist is one of the hottest job on the market right now. Demand for data science is huge and will only grow, and it seems like it will grow much faster than the actual number of data scientists. So if you want to make a career change and become a data scientist, now is the time. This book will guide you through the process. From my experience of working with multiple companies as a project manager, a data science consultant or a CTO, I was able to see the process of hiring data scientists and building data science teams. I know what’s important to land your first job as a data scientist, what skills you should acquire, what you should show during a job interview.
Author: Herbert Jones Publisher: ISBN: 9781647483043 Category : Computers Languages : en Pages : 134
Book Description
2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying
Author: Stylianos Kampakis Publisher: Apress ISBN: 1484254945 Category : Computers Languages : en Pages : 154
Book Description
Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics.Become skilled at thinking like a data scientist, without being one.Discover how to hire and manage data scientists.Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
Author: Andreas François Vermeulen Publisher: Apress ISBN: 148423054X Category : Computers Languages : en Pages : 821
Book Description
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You'll Learn Become fluent in the essential concepts and terminology of data science and data engineering Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers
Author: Ron S. Kenett Publisher: John Wiley & Sons ISBN: 1119570719 Category : Science Languages : en Pages : 136
Book Description
The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." —Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." —Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University
Author: Probyto Data Science and Consulting Pvt. Ltd. Publisher: BPB Publications ISBN: 9389423287 Category : Computers Languages : en Pages : 368
Book Description
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
Author: Andrew Park Publisher: Andrew Park ISBN: 9781801779449 Category : Languages : en Pages : 0
Book Description
★ 55% OFF for Bookstores! NOW at $ 21,97 instead of $ 31.97! ★ Are you interested in knowing more about the fascinating world of Data Science? Your Customers Will Love This Amazing Step-By-Step Guide! This book offers you the fundamental knowledge you need to get started, but keep in mind that no book or even teacher can do everything for you. You need to work hard by putting each building block in its place as you advance. Data Science is a massive field of study that requires years of learning and practice before you can master it. This shouldn't discourage you, however! Embrace it as a challenge that you can undertake in order to broaden your horizons and improve your knowledge of all that is Data Science and machine learning. Data Science is a highly complex topic that has continuously been developed for decades. It is constantly evolving, and it can be challenging to keep up with all the past, present, and future concepts. With that being said, this isn't supposed to discourage you from pursuing this field. To start out this guidebook, we are going to take a look at what Data Science is all about, why it is important, and why we would want to work with this process in the first place as well. We will then take some time in order to learn the lifecycle of Data Science, and how we need to go through a series of steps like the finding the right data, preparing the data, coming up with the right model, and more. All of this and more will be discussed in this guidebook so that you can go from start to finish with your own Data Science project. This is just the start of some of the amazing things that we are able to do when it is time to start on Data Science. We are able to spend our time looking at what machine learning is all about, the different types of machine learning, and how we are able to put it all together to makes sure that we can create the right algorithms and models when it is time to sort through our data and find the right patterns and insights in the process. In "The Essential Guide on Data Science" you will discover: What is Data Science? Why is Data Science So Important? The Benefits of Python Data Science The Lifecycle of Data Science The Importance of Visuals with Data Science A Look at Data Mining The Real-Life Applications of Data Science There are a lot of benefits that we are able to see when it comes to working on Data Science, and many companies in a lot of different industries are going to work with this in order to ensure that we will be able to handle how to work with their customers, how to beat out the competition, and so much more. When you are ready to work with the idea of Data Science, and you want to work with all of the different parts that are found with it, then make sure to check out this guidebook to help you get started. You can position yourself to use your deep knowledge and understanding of all the cutting-edge technologies obtained from this book to contribute to the growth of any company and land yourself a new high paying and rewarding job! Buy It NOW and Let Your Customers Get Addicted to This Amazing Book!
Author: Andrew Park
Author: Bart Baesens
Author: Hadley Wickham
Author: Przemek Chojecki
Author: Herbert Jones
Author: Erick Thompson
Author: Stylianos Kampakis
Author: Andreas François Vermeulen
Author: Ron S. Kenett
Author: Probyto Data Science and Consulting Pvt. Ltd.
Author: Andrew Park