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Everydata

Author : John H. Johnson
Publisher : Routledge
ISBN 13 : 1351861832
Total Pages : 247 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Everydata by : John H. Johnson

Download or read book Everydata written by John H. Johnson and published by Routledge. This book was released on 2016-10-14 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: While everyone is talking about "big data," the truth is that understanding the "little data"--the stats that underlie newspaper headlines, stock reports, weather forecasts, and so on--is what helps you make smarter decisions at work, at home, and in every aspect of your life. The average person consumes approximately 30 gigabytes of data every single day, but has no idea how to interpret it correctly. EVERYDATA explains, through the eyes of an expert economist and statistician, how to decipher the small bytes of data we consume in a day. EVERYDATA is filled with countless examples of people misconstruing data--with results that range from merely frustrating to catastrophic: The space shuttle Challenger exploded in part because the engineers were reviewing a limited sample set. Millions of women avoid caffeine during pregnancy because they interpret correlation as causation. Attorneys faced a $1 billion jury verdict because of outlier data. Each chapter highlights one commonly misunderstood data concept, using both realworld and hypothetical examples from a wide range of topics, including business, politics, advertising, law, engineering, retail, parenting, and more. You'll find the answer to the question--"Now what?"--along with concrete ways you can use this information to immediately start making smarter decisions, today and every day.

97 Things Every Data Engineer Should Know

Author : Tobias Macey
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062383
Total Pages : 263 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis 97 Things Every Data Engineer Should Know by : Tobias Macey

Download or read book 97 Things Every Data Engineer Should Know written by Tobias Macey and published by "O'Reilly Media, Inc.". This book was released on 2021-06-11 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

15 Math Concepts Every Data Scientist Should Know

Author : David Hoyle
Publisher : Packt Publishing Ltd
ISBN 13 : 1837631948
Total Pages : 510 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis 15 Math Concepts Every Data Scientist Should Know by : David Hoyle

Download or read book 15 Math Concepts Every Data Scientist Should Know written by David Hoyle and published by Packt Publishing Ltd. This book was released on 2024-08-16 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create more effective and powerful data science solutions by learning when, where, and how to apply key math principles that drive most data science algorithms Key Features Understand key data science algorithms with Python-based examples Increase the impact of your data science solutions by learning how to apply existing algorithms Take your data science solutions to the next level by learning how to create new algorithms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData science combines the power of data with the rigor of scientific methodology, with mathematics providing the tools and frameworks for analysis, algorithm development, and deriving insights. As machine learning algorithms become increasingly complex, a solid grounding in math is crucial for data scientists. David Hoyle, with over 30 years of experience in statistical and mathematical modeling, brings unparalleled industrial expertise to this book, drawing from his work in building predictive models for the world's largest retailers. Encompassing 15 crucial concepts, this book covers a spectrum of mathematical techniques to help you understand a vast range of data science algorithms and applications. Starting with essential foundational concepts, such as random variables and probability distributions, you’ll learn why data varies, and explore matrices and linear algebra to transform that data. Building upon this foundation, the book spans general intermediate concepts, such as model complexity and network analysis, as well as advanced concepts such as kernel-based learning and information theory. Each concept is illustrated with Python code snippets demonstrating their practical application to solve problems. By the end of the book, you’ll have the confidence to apply key mathematical concepts to your data science challenges.What you will learn Master foundational concepts that underpin all data science applications Use advanced techniques to elevate your data science proficiency Apply data science concepts to solve real-world data science challenges Implement the NumPy, SciPy, and scikit-learn concepts in Python Build predictive machine learning models with mathematical concepts Gain expertise in Bayesian non-parametric methods for advanced probabilistic modeling Acquire mathematical skills tailored for time-series and network data types Who this book is for This book is for data scientists, machine learning engineers, and data analysts who already use data science tools and libraries but want to learn more about the underlying math. Whether you’re looking to build upon the math you already know, or need insights into when and how to adopt tools and libraries to your data science problem, this book is for you. Organized into essential, general, and selected concepts, this book is for both practitioners just starting out on their data science journey and experienced data scientists.

40 Algorithms Every Data Scientist Should Know

Author : Jürgen Weichenberger
Publisher : BPB Publications
ISBN 13 : 9355519834
Total Pages : 655 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis 40 Algorithms Every Data Scientist Should Know by : Jürgen Weichenberger

Download or read book 40 Algorithms Every Data Scientist Should Know written by Jürgen Weichenberger and published by BPB Publications. This book was released on 2024-09-07 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Mastering AI and ML algorithms is essential for data scientists. This book covers a wide range of techniques, from supervised and unsupervised learning to deep learning and reinforcement learning. This book is a compass to the most important algorithms that every data scientist should have at their disposal when building a new AI/ML application. This book offers a thorough introduction to AI and ML, covering key concepts, data structures, and various algorithms like linear regression, decision trees, and neural networks. It explores learning techniques like supervised, unsupervised, and semi-supervised learning and applies them to real-world scenarios such as natural language processing and computer vision. With clear explanations, code examples, and detailed descriptions of 40 algorithms, including their mathematical foundations and practical applications, this resource is ideal for both beginners and experienced professionals looking to deepen their understanding of AI and ML. The final part of the book gives an outlook for more state-of-the-art algorithms that will have the potential to change the world of AI and ML fundamentals. KEY FEATURES ● Covers a wide range of AI and ML algorithms, from foundational concepts to advanced techniques. ● Includes real-world examples and code snippets to illustrate the application of algorithms. ● Explains complex topics in a clear and accessible manner, making it suitable for learners of all levels. WHAT YOU WILL LEARN ● Differences between supervised, unsupervised, and reinforcement learning. ● Gain expertise in data cleaning, feature engineering, and handling different data formats. ● Learn to implement and apply algorithms such as linear regression, decision trees, neural networks, and support vector machines. ● Creating intelligent systems and solving real-world problems. ● Learn to approach AI and ML challenges with a structured and analytical mindset. WHO THIS BOOK IS FOR This book is ideal for data scientists, ML engineers, and anyone interested in entering the world of AI. TABLE OF CONTENTS 1. Fundamentals 2. Typical Data Structures 3. 40 AI/ML Algorithms Overview 4. Basic Supervised Learning Algorithms 5. Advanced Supervised Learning Algorithms 6. Basic Unsupervised Learning Algorithms 7. Advanced Unsupervised Learning Algorithms 8. Basic Reinforcement Learning Algorithms 9. Advanced Reinforcement Learning Algorithms 10. Basic Semi-Supervised Learning Algorithms 11. Advanced Semi-Supervised Learning Algorithms 12. Natural Language Processing 13. Computer Vision 14. Large-Scale Algorithms 15. Outlook into the Future: Quantum Machine Learning

Everydata

Author : John H. Johnson
Publisher : Routledge
ISBN 13 : 9781629561011
Total Pages : 0 pages
Book Rating : 4.5/5 (61 download)

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Book Synopsis Everydata by : John H. Johnson

Download or read book Everydata written by John H. Johnson and published by Routledge. This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The average person consumes approximately 30 gigabytes of data every single day, but has no idea how to interpret it correctly. Everydata explains, through the eyes of an expert economist and statistician, how to correctly interpret all of the small bytes of data we consume in a day"--

The Art of Statistics

Author : David Spiegelhalter
Publisher : Basic Books
ISBN 13 : 1541618521
Total Pages : 359 pages
Book Rating : 4.5/5 (416 download)

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Book Synopsis The Art of Statistics by : David Spiegelhalter

Download or read book The Art of Statistics written by David Spiegelhalter and published by Basic Books. This book was released on 2019-09-03 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

SQL for Data Scientists

Author : Renee M. P. Teate
Publisher : John Wiley & Sons
ISBN 13 : 1119669391
Total Pages : 400 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis SQL for Data Scientists by : Renee M. P. Teate

Download or read book SQL for Data Scientists written by Renee M. P. Teate and published by John Wiley & Sons. This book was released on 2021-08-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset." Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!

Everydata

Author : John Johnson
Publisher :
ISBN 13 :
Total Pages : 224 pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Everydata by : John Johnson

Download or read book Everydata written by John Johnson and published by . This book was released on 2016 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: While everyone is talking about "big data," the truth is that understanding the "little data"--the stats that underlie newspaper headlines, stock reports, weather forecasts, and so on--is what helps you make smarter decisions at work, at home, and in every aspect of your life. The average person consumes approximately 30 gigabytes of data every single day, but has no idea how to interpret it correctly. EVERYDATA explains, through the eyes of an expert economist and statistician, how to decipher the small bytes of data we consume in a day. EVERYDATA is filled with countless examples of people misconstruing data--with results that range from merely frustrating to catastrophic: The space shuttle Challenger exploded in part because the engineers were reviewing a limited sample set. Millions of women avoid caffeine during pregnancy because they interpret correlation as causation. Attorneys faced a $1 billion jury verdict because of outlier data. Each chapter highlights one commonly misunderstood data concept, using both realworld and hypothetical examples from a wide range of topics, including business, politics, advertising, law, engineering, retail, parenting, and more. You'll find the answer to the question--"Now what?"--along with concrete ways you can use this information to immediately start making smarter decisions, today and every day.

Storytelling with Data

Author : Cole Nussbaumer Knaflic
Publisher : John Wiley & Sons
ISBN 13 : 1119002265
Total Pages : 284 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Storytelling with Data by : Cole Nussbaumer Knaflic

Download or read book Storytelling with Data written by Cole Nussbaumer Knaflic and published by John Wiley & Sons. This book was released on 2015-10-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

All Data Are Local

Author : Yanni Alexander Loukissas
Publisher : MIT Press
ISBN 13 : 0262039664
Total Pages : 267 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis All Data Are Local by : Yanni Alexander Loukissas

Download or read book All Data Are Local written by Yanni Alexander Loukissas and published by MIT Press. This book was released on 2019-04-30 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.

Beyond Basic Statistics

Author : Kristin H. Jarman
Publisher : John Wiley & Sons
ISBN 13 : 1118856120
Total Pages : 200 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Beyond Basic Statistics by : Kristin H. Jarman

Download or read book Beyond Basic Statistics written by Kristin H. Jarman and published by John Wiley & Sons. This book was released on 2015-04-22 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques. Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life’s important questions. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features: Plentiful examples throughout aimed to strengthen readers’ understanding of the statistical concepts and methods A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression A case study in each chapter that illustrates the use of the presented techniques Highlights of well-known shortcomings that can lead to false conclusions An introduction to advanced techniques such as validation and bootstrapping Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.

Data Analysis Using SQL and Excel

Author : Gordon S. Linoff
Publisher : John Wiley & Sons
ISBN 13 : 0470952520
Total Pages : 698 pages
Book Rating : 4.4/5 (79 download)

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Book Synopsis Data Analysis Using SQL and Excel by : Gordon S. Linoff

Download or read book Data Analysis Using SQL and Excel written by Gordon S. Linoff and published by John Wiley & Sons. This book was released on 2010-09-16 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.

Data Feminism

Author : Catherine D'Ignazio
Publisher : MIT Press
ISBN 13 : 0262358530
Total Pages : 328 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Data Feminism by : Catherine D'Ignazio

Download or read book Data Feminism written by Catherine D'Ignazio and published by MIT Press. This book was released on 2020-03-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

Knowledge Discovery from Data Streams

Author : Joao Gama
Publisher : CRC Press
ISBN 13 : 1439826129
Total Pages : 256 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Knowledge Discovery from Data Streams by : Joao Gama

Download or read book Knowledge Discovery from Data Streams written by Joao Gama and published by CRC Press. This book was released on 2010-05-25 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents

Machine Learning with Python Cookbook

Author : Chris Albon
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491989335
Total Pages : 305 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Machine Learning with Python Cookbook by : Chris Albon

Download or read book Machine Learning with Python Cookbook written by Chris Albon and published by "O'Reilly Media, Inc.". This book was released on 2018-03-09 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models

Executing Data Quality Projects

Author : Danette McGilvray
Publisher : Elsevier
ISBN 13 : 0080558399
Total Pages : 353 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Executing Data Quality Projects by : Danette McGilvray

Download or read book Executing Data Quality Projects written by Danette McGilvray and published by Elsevier. This book was released on 2008-09-01 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her "Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations.* Includes numerous templates, detailed examples, and practical advice for executing every step of the "Ten Steps approach.* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

Data Warehousing

Author : Mark Humphries
Publisher : Prentice Hall Professional
ISBN 13 : 9780130809025
Total Pages : 384 pages
Book Rating : 4.8/5 (9 download)

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Book Synopsis Data Warehousing by : Mark Humphries

Download or read book Data Warehousing written by Mark Humphries and published by Prentice Hall Professional. This book was released on 1999 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: PLEASE PROVIDE COURSE INFORMATION PLEASE PROVIDE