Getting Started With Data Science Making Sense Of Data With Analytics

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Getting Started with Data Science Making Sense of Data with Analytics

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Author by : Murtaza Haider
Languange Used : English, France, Spanish, Italia and chinese
Page : 250
Isbn : 9780133991024
Identifier : 0133991024
Release : 2015-07-16
Publisher by : IBM Press
Category : Computers
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Description : Read Now Getting Started With Data Science by Murtaza Haider and you can download with pub, pdf, txt, doc, and more file format with free account. master data analytics hands-on by solving fascinating problems you'll actually enjoy! harvard business review recently called data science "the sexiest job of the 21st century." it's not just sexy: for millions of managers, analysts, and students who need to solve real business problems, it's indispensable. unfortunately, there's been nothing easy about learning data science-until now. getting started with data science takes its inspiration from worldwide best-sellers like freakonomics and malcolm gladwell's outliers: it teaches through a powerful narrative packed with unforgettable stories. murtaza haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. everything's software and platform agnostic, so you can learn data science whether you work with r, stata, spss, or sas. best of all, haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. you'll master data science by answering fascinating questions, such as: * are religious individuals more or less likely to have extramarital affairs? * do attractive professors get better teaching evaluations? * does the higher price of cigarettes deter smoking? * what determines housing prices more: lot size or the number of bedrooms? * how do teenagers and older people differ in the way they use social media? * who is more likely to use online dating services? * why do some purchase iphones and others blackberry devices? * does the presence of children influence a family's spending on alcohol? for each problem, you'll walk through defining your question and the answers you'll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Getting Started with Data Science Making Sense of Data with Analytics

Download Getting Started With Data Science Book or Ebook File with PDF Epub Audio and Full format File

Author by : Murtaza Haider
Languange Used : English, France, Spanish, Italia and chinese
Page : 400
Isbn : 0133991237
Identifier : 9780133991239
Release : 2015-12-14
Publisher by : IBM Press
Category : Business & Economics
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Description : Read Now Getting Started With Data Science by Murtaza Haider and you can download with pub, pdf, txt, doc, and more file format with free account. master data analytics hands-on by solving fascinating problems you’ll actually enjoy! harvard business review recently called data science “the sexiest job of the 21st century.” it’s not just sexy: for millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. unfortunately, there’s been nothing easy about learning data science–until now. getting started with data science takes its inspiration from worldwide best-sellers like freakonomics and malcolm gladwell’s outliers: it teaches through a powerful narrative packed with unforgettable stories. murtaza haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. everything’s software and platform agnostic, so you can learn data science whether you work with r, stata, spss, or sas. best of all, haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. you’ll master data science by answering fascinating questions, such as: • are religious individuals more or less likely to have extramarital affairs? • do attractive professors get better teaching evaluations? • does the higher price of cigarettes deter smoking? • what determines housing prices more: lot size or the number of bedrooms? • how do teenagers and older people differ in the way they use social media? • who is more likely to use online dating services? • why do some purchase iphones and others blackberry devices? • does the presence of children influence a family’s spending on alcohol? for each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Getting Started with Data Science Making Sense of Data with Analytics

Download Getting Started With Data Science Book or Ebook File with PDF Epub Audio and Full format File

Author by : Murtaza Haider
Languange Used : English, France, Spanish, Italia and chinese
Page : 233
Isbn : 9780133991246
Identifier : 0133991245
Release : 2016
Publisher by : no defined
Category : Business enterprises
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Principles of Data Science

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Author by : Sinan Ozdemir
Languange Used : English, France, Spanish, Italia and chinese
Page : 388
Isbn : 1785888927
Identifier : 9781785888922
Release : 2016-12-16
Publisher by : Packt Publishing Ltd
Category : Computers
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Description : Read Now Principles Of Data Science by Sinan Ozdemir and you can download with pub, pdf, txt, doc, and more file format with free account. learn the techniques and math you need to start making sense of your data about this book enhance your knowledge of coding with data science theory for practical insight into data science and analysis more than just a math class, learn how to perform real-world data science tasks with r and python create actionable insights and transform raw data into tangible value who this book is for you should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of r/python as well as pseudo code. you should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. if you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. what you will learn get to know the five most important steps of data science use your data intelligently and learn how to handle it with care bridge the gap between mathematics and programming learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results build and evaluate baseline machine learning models explore the most effective metrics to determine the success of your machine learning models create data visualizations that communicate actionable insights read and apply machine learning concepts to your problems and make actual predictions in detail need to turn your skills at programming into effective data science skills? principles of data science is created to help you join the dots between mathematics, programming, and business analysis. with this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. with a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. you'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. style and approach this is an easy-to-understand and accessible tutorial. it is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Digital Marketing Analytics Making Sense of Consumer Data in a Digital World

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Author by : Chuck Hemann
Languange Used : English, France, Spanish, Italia and chinese
Page : 384
Isbn : 0133150925
Identifier : 9780133150926
Release : 2013-04-10
Publisher by : Que Publishing
Category : Business & Economics
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Description : Read Now Digital Marketing Analytics by Chuck Hemann and you can download with pub, pdf, txt, doc, and more file format with free account. distill 100%–usable max-profit knowledge from your digital data. do it now! why hasn’t all that data delivered a whopping competitive advantage? because you’ve barely begun to use it, that’s why! good news: neither have your competitors. it’s hard! but digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you. chuck hemann and ken burbary will help you chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results! scope it out, pick your tools, learn to listen, get the metrics right, and then distill your digital data for maximum value for everything from r&d to crm to social media marketing! • prioritize—because you can’t measure, listen to, and analyze everything • use analysis to craft experiences that profoundly reflect each customer’s needs, expectations, and behaviors • measure real social media roi: sales, leads, and customer satisfaction • track the performance of all paid, earned, and owned social media channels • leverage “listening data” way beyond pr and marketing: for strategic planning, product development, and hr • start optimizing web and social content in real time • implement advanced tools, processes, and algorithms for accurately measuring influence • integrate paid and social data to drive more value from both • make the most of surveys, focus groups, and offline research synergies • focus new marketing and social media investments where they’ll deliver the most value foreword by scott monty global head of social media, ford motor company

Developing Analytic Talent Becoming a Data Scientist

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Author by : Vincent Granville
Languange Used : English, France, Spanish, Italia and chinese
Page : 336
Isbn : 1118810090
Identifier : 9781118810095
Release : 2014-03-24
Publisher by : John Wiley & Sons
Category : Computers
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Description : Read Now Developing Analytic Talent by Vincent Granville and you can download with pub, pdf, txt, doc, and more file format with free account. learn what it takes to succeed in the the most in-demand tech job harvard business review calls it the sexiest tech job of the 21st century. data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented it professionals. data science involves extracting, creating, and processing data to turn it into business value. with over 15 years of big data, predictive modeling, and business analytics experience, author vincent granville is no stranger to data science. in this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code. the applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one. explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists features job interview questions, sample resumes, salary surveys, and examples of job ads case studies explore how data science is used on wall street, in botnet detection, for online advertising, and in many other business-critical situations developing analytic talent: becoming a data scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates.

Data Science For Dummies

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Author by : Lillian Pierson
Languange Used : English, France, Spanish, Italia and chinese
Page : 384
Isbn : 1119327636
Identifier : 9781119327639
Release : 2017-03-06
Publisher by : John Wiley & Sons
Category : Computers
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Description : Read Now Data Science For Dummies by Lillian Pierson and you can download with pub, pdf, txt, doc, and more file format with free account. discover how data science can help you gain in-depth insight into your business - the easy way! jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. data science for dummies is the perfect starting point for it professionals and students who want a quick primer on all areas of the expansive data science space. with a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. if you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. while this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. here's what to expect: provides a background in big data and data engineering before moving on to data science and how it's applied to generate value includes coverage of big data frameworks like hadoop, mapreduce, spark, mpp platforms, and nosql explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the internet of things details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate it's a big, big data world out there--let data science for dummies help you harness its power and gain a competitive edge for your organization.

Data Science from Scratch First Principles with Python

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Author by : Joel Grus
Languange Used : English, France, Spanish, Italia and chinese
Page : 330
Isbn : 1491904402
Identifier : 9781491904404
Release : 2015-04-14
Publisher by : "O'Reilly Media, Inc."
Category : Computers
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Description : Read Now Data Science From Scratch by Joel Grus and you can download with pub, pdf, txt, doc, and more file format with free account. data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. in this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. if you have an aptitude for mathematics and some programming skills, author joel grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. today’s messy glut of data holds answers to questions no one’s even thought to ask. this book provides you with the know-how to dig those answers out. get a crash course in python learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science collect, explore, clean, munge, and manipulate data dive into the fundamentals of machine learning implement models such as k-nearest neighbors, naive bayes, linear and logistic regression, decision trees, neural networks, and clustering explore recommender systems, natural language processing, network analysis, mapreduce, and databases

Making Sense of Multivariate Data Analysis An Intuitive Approach

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Author by : John Spicer
Languange Used : English, France, Spanish, Italia and chinese
Page : 233
Isbn : 9781412904018
Identifier : 1412904013
Release : 2005
Publisher by : SAGE
Category : Mathematics
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Description : Read Now Making Sense Of Multivariate Data Analysis by John Spicer and you can download with pub, pdf, txt, doc, and more file format with free account. ′this book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research′ _c. y. joanne peng, indiana university at bloomington ′this book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. the author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). these points are valuable even for readers who have extensive training with multivariate analyses′ _jenn-yun tein, arizona state university

Data Science for Business What You Need to Know about Data Mining and Data-Analytic Thinking

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Author by : Foster Provost
Languange Used : English, France, Spanish, Italia and chinese
Page : 414
Isbn : 144937428X
Identifier : 9781449374280
Release : 2013-07-27
Publisher by : "O'Reilly Media, Inc."
Category : Computers
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Description : Read Now Data Science For Business by Foster Provost and you can download with pub, pdf, txt, doc, and more file format with free account. written by renowned data science experts foster provost and tom fawcett, data science for business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. this guide also helps you understand the many data-mining techniques in use today. based on an mba course provost has taught at new york university over the past ten years, data science for business provides examples of real-world business problems to illustrate these principles. you’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. you’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. understand how data science fits in your organization—and how you can use it for competitive advantage treat data as a business asset that requires careful investment if you’re to gain real value approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way learn general concepts for actually extracting knowledge from data apply data science principles when interviewing data science job candidates

Data Science at the Command Line Facing the Future with Time-Tested Tools

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Author by : Jeroen Janssens
Languange Used : English, France, Spanish, Italia and chinese
Page : 212
Isbn : 1491947829
Identifier : 9781491947821
Release : 2014-09-25
Publisher by : "O'Reilly Media, Inc."
Category : Computers
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Description : Read Now Data Science At The Command Line by Jeroen Janssens and you can download with pub, pdf, txt, doc, and more file format with free account. this hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. you’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. to get you started—whether you’re on windows, os x, or linux—author jeroen janssens introduces the data science toolbox, an easy-to-install virtual environment packed with over 80 command-line tools. discover why the command line is an agile, scalable, and extensible technology. even if you’re already comfortable processing data with, say, python or r, you’ll greatly improve your data science workflow by also leveraging the power of the command line. obtain data from websites, apis, databases, and spreadsheets perform scrub operations on plain text, csv, html/xml, and json explore data, compute descriptive statistics, and create visualizations manage your data science workflow using drake create reusable tools from one-liners and existing python or r code parallelize and distribute data-intensive pipelines using gnu parallel model data with dimensionality reduction, clustering, regression, and classification algorithms

Doing Data Science Straight Talk from the Frontline

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Author by : Cathy O'Neil
Languange Used : English, France, Spanish, Italia and chinese
Page : 408
Isbn : 144936389X
Identifier : 9781449363895
Release : 2013-10-09
Publisher by : "O'Reilly Media, Inc."
Category : Computers
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Description : Read Now Doing Data Science by Cathy O'Neil and you can download with pub, pdf, txt, doc, and more file format with free account. now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. but how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? this insightful book, based on columbia university’s introduction to data science class, tells you what you need to know. in many of these chapter-long lectures, data scientists from companies such as google, microsoft, and ebay share new algorithms, methods, and models by presenting case studies and the code they use. if you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. topics include: statistical inference, exploratory data analysis, and the data science process algorithms spam filters, naive bayes, and data wrangling logistic regression financial modeling recommendation engines and causality data visualization social networks and data journalism data engineering, mapreduce, pregel, and hadoop doing data science is collaboration between course instructor rachel schutt, senior vp of data science at news corp, and data science consultant cathy o’neil, a senior data scientist at johnson research labs, who attended and blogged about the course.