The Art of Data Science

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Publisher :
ISBN 13 : 9781365061462
Total Pages : 170 pages
Book Rating : 4.69/5 ( download)

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Book Synopsis The Art of Data Science by : Roger D. Peng

Download or read book The Art of Data Science written by Roger D. Peng and published by . This book was released on 2016-06-08 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science."--Leanpub.com.

Data Science for Beginners

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Publisher :
ISBN 13 : 9781914167997
Total Pages : 394 pages
Book Rating : 4.96/5 ( download)

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Book Synopsis Data Science for Beginners by : Andrew Park

Download or read book Data Science for Beginners written by Andrew Park and published by . This book was released on 2021-02-09 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! Now at $49.95 instead of $59.95! ★ Your Customers Will Never Stop To Use This Complete Guide! Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: ● Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops ● Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism ● Discover the importance of Data Science and how to use it in real-world situations ● Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you ● Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn ● Discover how companies can improve their business through practical examples and explanations ● And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform. Whether you are a software engineer or a project manager, jump to the next level by developing a data-driven approach and learning how to define a data-driven vision of your business! Order Your Copy of the Bundle and Let Your Customers Start Their New Career Path Today!

Communicating with Data

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Publisher : Oxford University Press
ISBN 13 : 0198862741
Total Pages : 350 pages
Book Rating : 4.41/5 ( download)

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Book Synopsis Communicating with Data by : Deborah Nolan

Download or read book Communicating with Data written by Deborah Nolan and published by Oxford University Press. This book was released on 2021 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data.

Data Science for Beginners

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Publisher : Independently Published
ISBN 13 :
Total Pages : 732 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Data Science for Beginners by : Andrew Park

Download or read book Data Science for Beginners written by Andrew Park and published by Independently Published. This book was released on 2020-01-26 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the world of Python, Data Analysis, Machine Learning and Data Science with this comprehensive 4-in-1 bundle. Do you want to learn more about the amazing world of Data Science? Or are you interested in becoming a Python geek? Then keep reading. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and Data Science, from basic code and concepts to complex Neural Networks and data manipulation. Inside, you'll discover everything you need to know to get started with Python and Data Science, and begin your journey to success! In book one, PYTHON FOR BEGINNERS, you will learn: How to install Python What are the different Python Data Types, Variables and Basic Operators Data Structures, Functions and Files Conditional and Loops in Python Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools and Exception Handling An application to Decision Trees And Much More! In book two, PYTHON FOR DATA ANALYSIS, you will learn: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Neural Network The 7 Python libraries that make Python one of the best choices for Data Analysis How Data Visualization and Matplotlib can help you to understand the data you are working with. Some of the main industries that are using data to improve their business with 14 real-world applications And Much More! In book three, PYTHON MACHINE LEARNING, you will learn: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Machine learning training models, Regression techniques and Linear Regression in Python How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python Artificial Neural Networks And Much More! And in book four, PYTHON DATA SCIENCE, you will learn: What Data Science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises The 7 most important algorithms and models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! Whether you're a complete beginner or a programmer looking to improve his skillset, Data Science for Beginners is your all-in-one solution to mastering the world of Python and Data Science. Would you like to know more?Scroll Up and Click on the BUY NOW Button to Get Your Copy!

The Art and Science of Analyzing Software Data

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Publisher : Elsevier
ISBN 13 : 0124115438
Total Pages : 672 pages
Book Rating : 4.39/5 ( download)

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Book Synopsis The Art and Science of Analyzing Software Data by : Christian Bird

Download or read book The Art and Science of Analyzing Software Data written by Christian Bird and published by Elsevier. This book was released on 2015-09-02 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry

Data Science Using Python and R

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Publisher : John Wiley & Sons
ISBN 13 : 1119526817
Total Pages : 256 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Data Science Using Python and R by : Chantal D. Larose

Download or read book Data Science Using Python and R written by Chantal D. Larose and published by John Wiley & Sons. This book was released on 2019-04-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.

Data Science Programming All-in-One For Dummies

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Publisher : John Wiley & Sons
ISBN 13 : 1119626110
Total Pages : 768 pages
Book Rating : 4.14/5 ( download)

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Book Synopsis Data Science Programming All-in-One For Dummies by : John Paul Mueller

Download or read book Data Science Programming All-in-One For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2020-01-09 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!

The Art of Data-Driven Business

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Publisher : Packt Publishing Ltd
ISBN 13 : 180461873X
Total Pages : 314 pages
Book Rating : 4.38/5 ( download)

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Book Synopsis The Art of Data-Driven Business by : Alan Bernardo Palacio

Download or read book The Art of Data-Driven Business written by Alan Bernardo Palacio and published by Packt Publishing Ltd. This book was released on 2022-12-02 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leaders Key FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook Description One of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get. The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company. You'll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you'll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you'll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods. By the end of this Python book, you'll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you've learned in the real world. What you will learnCreate effective dashboards with the seaborn libraryPredict whether a customer will cancel their subscription to a serviceAnalyze key pricing metrics with pandasRecommend the right products to your customersDetermine the costs and benefits of promotionsSegment your customers using clustering algorithmsWho this book is for This book is for data scientists, machine learning engineers and developers, data engineers, and business decision makers who want to apply data science for business process optimization and develop the skills needed to implement data science projects in marketing, sales, pricing, customer success, ad tech, and more from a business perspective. Other professionals looking to explore how data science can be used to improve business operations, as well as individuals with technical skills who want to back their technical proposal with a strong business case will also find this book useful.

Data Science for Beginners

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Author :
Publisher :
ISBN 13 :
Total Pages : 396 pages
Book Rating : 4.32/5 ( download)

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Book Synopsis Data Science for Beginners by : Andrew Park

Download or read book Data Science for Beginners written by Andrew Park and published by . This book was released on 2021-12-22 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism Discover the importance of Data Science and how to use it in real-world situations Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn Discover how companies can improve their business through practical examples and explanations And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform, even if you have never seen a line of code in your life. Jump to the next level by learning the basics of programming that will allow you to develop a data-driven approach! Order Your Copy of the Bundle Now and Start to Develop New Valuable Skills Today!

Encyclopedia of Data Science and Machine Learning

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Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.