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Getting Started with Data Science: Making Sense of Data with Analytics by Murtaza Haider

• Getting Started with Data Science: Making Sense of Data with Analytics
• Murtaza Haider
• Page: 400
• Format: pdf, ePub, mobi, fb2
• ISBN: 9780133991024
• Publisher: IBM Press

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Ebook for dot net free download Getting Started with Data Science: Making Sense of Data with Analytics

Harvard Business Review recently called data science "The Sexiest Job of the 21st Century." It's not just sexy: for millions of managers and students who need to solve business problems with big data, it's indispensable. Unfortunately, there's been nothing sexy about learning data science -- until now. Getting Started with Data Science takes its approach from worldwide best-sellers like Freakonomics and the books of Malcolm Gladwell: it teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers careful, jargon-free coverage of basic theory and technique, backed with plenty of clear examples and practice opportunities. Everything's software and platform independent, so you can learn what you need whether you work with R, Stata, SPSS, SAS, or another toolset. Best of all, Haider teaches a crucial skillset most academic data science books ignore: how to transform data into narratives, graphics, and tables that make it vivid and actionable. Every chapter is built around a real research challenge, so you'll always know why you're doing what you're doing. You'll master data science by answering fascinating questions like: Are child safety seats safer for children than regular seat belts? Which married parents are likelier to have affairs: fathers or mothers? Is CEO compensation independent of a firm's profitability? Do attractive professors get better teaching evaluations? What induces teenagers to start smoking? What determines housing prices more: house size or location? How do teenagers and older people differ in how they use social media? Do risk-averse and risk-prone individuals differ in their purchases of big-ticket items? For each problem, you'll walk through identifying the right data and methods, creating summary statistics, describing and visualizing findings, and seeing how others have handled the challenge. In advanced chapters, you'll also learn sophisticated statistical modeling techniques. Throughout, the focus is on data: finding it, using it, and powerfully communicating its meaning.

Using R for Data Science - Master's in Data Science
needs to make sense of data, really—can use R for statistical analysis, data visualization, Here's how some big names are making R work for them. If, however, you're just getting started, here are some online courses that will have you The Analytics Edge from MITx: Devote 10-15 hours to this course for 12 weeks  Getting Started with Data Science: Making Sense of Data - Safari
Instantly access Getting Started with Data Science: Making Sense of Data with Analytics by Murtaza Haider. Start your free 10-day trial of Safari. Beyond the hype: Big data concepts, methods, and analytics
We make the case for new statistical techniques for big data. working on a book, Getting Started with Data Science: Making Sense of Data  Getting Started with Data Science: Making Sense of - IBM Press
Unfortunately, there's been nothing sexy about learning data science -- until now. Getting Started with Data Science: Making Sense of Data with Analytics. Analytics For All, No Data Scientists Needed - InformationWeek
McKinsey & Co. exclaims that advanced big data analytics, driven partly by the There's also an explosion of tools and tactics to help knowledge workers tap into and make sense of it all. We really are just getting started. How to Get Started in Data Science - Hortonworks
Some thoughts from Hortonworks resident Data Scientist on getting started with data science. some partial background and are looking to make the transition into data science. In other sense how should I utilize my knowledge to get a tag of data scientist. Magellan: Geospatial Analytics on Spark.

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