Free Ebook Practical Data Science with R

Free Ebook Practical Data Science with R

This publication is served in soft documents kinds. You could download it. One that will certainly influence you to read this publication is that it can be your personal selection to earn far better feels. Your life is your own. And selecting this Practical Data Science With R as your reading product is also your selection. Yet here, we truly advise you to read this publication. You could find exactly what the elements we present. Simply get this book as well as review it, so you can get the factors of why you have to check out.

Practical Data Science with R

Free Ebook Practical Data Science with R

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About the Author

Nina Zumel co-founded Win-Vector, a data science consulting firm in San Francisco. She holds a PH.D. in robotics from Carnegie Mellon and was a content developer for EMC's Data Science and Big Data Analytics Training Course. Nina also contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.John Mount co-founded Win-Vector, a data science consulting firm in San Francisco. He has a Ph.D. in computer science from Carnegie Mellon and over 15 years of applied experience in biotech research, online advertising, price optimization and finance. He contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.

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Product details

Paperback: 389 pages

Publisher: Manning; 1st edition (April 13, 2014)

Language: English

ISBN-10: 1617291560

ISBN-13: 978-1617291562

Product Dimensions:

7.3 x 1 x 9.1 inches

Shipping Weight: 1.5 pounds (View shipping rates and policies)

Average Customer Review:

4.2 out of 5 stars

36 customer reviews

Amazon Best Sellers Rank:

#355,384 in Books (See Top 100 in Books)

Practical Data Science is a fun interesting book.. There are parts that lost me.... like watching a ball under the three shells kind of thing... but-- the 70% of the book that I DID get is remarkable. I learned many things that I will put to use. Well worth the price of the book. For example-- I loved the lookup vectors to change values.. very interesting graphs. This book does not waste your time. Hopefully soon I can grasp everything. Good job. I recommend for all R users. I love that the examples are about real business situations and not plant life.

This book is what I was looking for for my new job as a Credit Risk Data Modeler (basically data science applied to credit problems). It's coverage is broad, but deep and applied enough that I have been able to apply its contents in my day-to-day work. I look forward to a second edition which will hopefully rectify the following:Earlier in the book it seemed the authors took great pains to explain in layman's terms the various statistical elements of the topic they were covering. They provided very clear and meaningful explanations which made a lot of sense of complex topics. But later in the book it seemed that that approach largely went out the window and they started using more technical boiler plate to describe the various statistical tests and procedures. Rather than perhaps give the technical boilerplate (as you'd see it in a textbook) and then elaborate on it with a more human-centric explanation, they would just leave it at the nearly impervious technical description and then proceed to explain how to conduct the test/procedure/etc in R. But without understanding of what you're trying to accomplish and why, it's hard to write the code to actually do it. Keep in mind that I'm relatively well prepared for this book too, having had as much stats and econometrics as I could fit into my four-year degree. If I found some sections of the book too technical to understand then it seems likely that the book would benefit from some additional explanation and discussion in those later sections.Also, I have a good deal of "boots on the ground" experience with this book in my attempts to apply it in my daily work. I've found that it is useful, but could be more useful if there was more discussion of various practical problems. For instance, much of my work is focused on producing a predictive model of likelihood of charge-off. I.e., if we approve and fund this application, how likely is it to perform or charge-off. The book shares some high-level approaches to finding problems in data (using plots and summaries), fixing those problems using various techniques, selecting variables, and how to conduct the statistical modeling (logistic in my case). But it fails to really tie those areas together beyond the high-level. For instance, what are the assumptions of a logistic regression? How do you resolve issues in your data to ensure that you meet those assumptions and can perform a valid logistic regression? How do you really select variables when you're faced with at least 20 possibilities (and potentially many many more if you count interaction terms, unfixed variables, and variables which have been fixed in different ways)?I suppose, for what it was, that it is "mission accomplished." I'd just like to see a lot more. Perhaps there's need for a second volume? Perhaps "Advanced Practical Data Science with R?" Either this book could have a second edition with a lot more content covering finding data problems, resolving those problems intelligently (for instance, resolving missing data is basically left as "either drop the effected records" or "use the mean as a replacement or the missing value," but there are alternative methods which may be more suitable), what data problems will cause issues in OLS regression, logistic regression, and machine learning; And how to practically select variables and a model. I feel like the book gave me some tools to apply (like a small box of tools you might purchase from a hardware store), but left a lot out. So now I'm in deep water trying to figure out why my logistic regression isn't predictive enough and what I can do about it. Is it the data and how I fixed variables? Is it the variables I've selected? Should I have used automated variable selection techniques? Or just manually tried different variables? How does an experienced practitioner approach these problems? I know they iterate: explore data, clean data, select variables, select model, test model, look at data, change data, change variables, etc... but practically speaking what does it look like? In the book they offer a hand-coded basic variable selection script, and mention that one could also use stepwise variable selection. In the real world I'm reasonably sure that this is not actually done--mostly because their selection script does about as well as stepwise at selecting appropriate variables. There are many other better ways of selecting variables, I've discovered, and I wish that they'd discussed some of those ways (pros and cons), and shown how to conduct them in a meaningful fashion. Same thing with building a model. In my case, I have a whole bunch of variables, limited data (about 2000 records, with the desired outcome only occurring in 120 of those), and the automated tools (various R packages I've discovered and applied) either take a long time to run and/or yield poor results. But if not automated tools then what? Manually add variables and ANOVA test the difference between the first and second model?I'd just like more...more discussion and elaboration and examples of how practical data science is conducted. This book seems like it does a fantastic job as an introduction to the topic, but you'll quickly find that you'll be in deep water without a clue how to swim--as in my case. You'll be left to your own devices, and find yourself wishing, as I do, that there was more in the book (or another book) that I could study after this one which would help take me from beginner data scientist to intermediate.Overall, I'm very glad I bought and read the book.

Hands-on textbook that covers pretty much all aspects of data science (with keen attention to business demands). Importantly, it doesn't shy away from discussing statistical details behind the most common routines in machine learning, which I really appreciated as I was tired of typical DS books that take a black box approach that just shows "how" without explaining the "why". I think it's worth having a copy of this book irrespective of whether you are a beginner to data science or a veteran. Highly recommended!If you buy a hard copy, I would also recommend having a look at the colorful figures in the companion soft copy of the book.

Love this book. Any one interested in data science should get this hands-on experiential learning book.

The book has a lot of good examples and gets you jump started on being productive.

Great very detail book! I am an analytics professional looking to starting using R programming to leverage my data the best way I can.

Good Read

An awesome book that's helped me on occasion with my coursework and my job.

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Download Ebook Game On: Energize Your Business with Social Media GamesBy Jon Radoff

Download Ebook Game On: Energize Your Business with Social Media GamesBy Jon Radoff

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Game On: Energize Your Business with Social Media GamesBy Jon Radoff

Download Ebook Game On: Energize Your Business with Social Media GamesBy Jon Radoff

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A never-before published look at the many possibilities of social game development

As one of the few entrepreneurs in the world with expertise building both social media and games, author Jon Radoff brings a one-of-a-kind perspective to this unique book. He shows that games are more than a profitable form of entertainment?the techniques of social games can be used to enhance the quality of online applications, social media and a wide range of other consumer and business experiences. With this book, you?ll explore how social games can be put to work for any business and examine why they work at all. The first part of explains what makes games fun, while the second part reviews the process and details of game design.

• Looks at how games are the basis for many everyday functions and explains how techniques of social games can be used by businesses as money-making tools
• Drills down the process of game design while focusing on the design, analysis, and creation of games
• Features screen shots, diagrams and explanations to illuminate key concepts, accessible to anyone regardless of game playing or design experience
• Reviews what works and what doesn?t using a range of real-world scenarios as examples
• Author Jon Radoff has a unique blend of experiences creating games, Internet-based social media, and Web technology.

Game On is not playing around. Discover how social media games make money?and how you can enhance your business using games. Amazon.com Exclusive Article: “8 Businesses Changing the World with Game Mechanics” by Jon Radoff, Author of Game On: Energize Your Business with Social Media Games Author Jon Radoff People are playing games more than ever before--but many of those games are less obvious than you might think. Games have influenced education, healthcare, retail, and consumer industries. Here are a few companies doing things with game mechanics that you might not have suspected, as well as questions you can ask yourself about your own business: 1) LinkedIn.com The popular business networking website has turned networking into a game. People love collecting things--and on LinkedIn, the connections you form with other people are like a collection of virtual business cards. The more connections you have, the more you “win.” On LinkedIn, the rewards are social status; but collecting is fun in a wide range of businesses. What could you enable your customers to collect? 2) Dollar Tree Exploration is fun, and many popular digital and social games are about finding hidden places, secret treasures and unusual artifacts. Dollar Tree attracts people with the premise that everything will be only $1 --but it’s the act of exploring that is fun for many people. Could your company give your customers the thrill of exploration? Better yet, could you let people use social media to spread the word of their discoveries? 3) Cold Stone Creamery In games like World of Warcraft, many people enjoy “crafting” their own products. Creativity is fun--even when it comes from a well-worn process. Combine it with the pleasure of eating great ice cream, and you’ll understand part of what makes Cold Stone Creamery interesting. Beyond Cold Stone Creamery, other companies as diverse as Brighton (jewelry and accessories) and Build-a-Bear Workshop (stuffed bears) are tapping into the desire for personal, automated crafting to turn shopping and dining into an experience. How can you allow your customers to craft? 4) Upromise Upromise has turned saving money for college into a game--it’s about discovering the products and companies that allow you to earn extra cash to invest in your kids’ education. It’s also a social game: you enroll your family, and make college savings a team effort. What makes it work is the continuous sense of progress. How can you give customers a sense that they’re always achieving something? 5) Nike Nike has gone beyond being a footwear company--they’re about providing a complete experience that’s about running and fashion. Using social technology like Nike+, an application that let’s you record your runs and share them with others around the world, Nike promotes a sense of community with their brand. Likewise, Nike.ID allows customers to design their own look, and share them with others. By integrating multiple elements of competition, discovery and personalization into their products, it’s as if you’re playing the World of Nike game. How could you create an immersive experience for your customers? 6) Groupon For many people, collecting coupons is more than a way to save money--it’s about discovery and reward. Groupon has taken it to the next level by making it a social experience as well: when you find an activity you like, you can save a few dollars while also uncovering an activity that you and your friends can enjoy together. How can you market your business better by turning a solitary experience into a social activity? 7) MeYouHealth Successful games feature many small rewards to keep you focused and engaged. One of the largest areas where this could have a huge and positive effect on society is our health--but let’s face it: healthcare is rarely fun. MeYouHealth, a subsidiary of Healthways, is creating games and applications that get people to think about well-being by focusing on the small steps you can take to improve your life. How can you give your customers a pathway to success, one small (but rewarding) step at a time? 8) St. Augustine Pirate & Treasure Museum Almost every game is about learning: figuring out a strategy, improving a skill, or gaining an understanding of a set of rules; yet attempts at integrating learning with games have often yielded less-than-engaging results. However, when learning is made fun by crafting an experience enriched by story and discovery, the results can be spectacular. A great example of this is the St. Augustine Pirate & Treasure Museum, which has turned learning about pirates into a fully immersive adventure. Rather than have your customers look at a world, how can you have them customers experience it?

• Amazon Sales Rank: #1473132 in Books
• Published on: 2011-04-12
• Original language: English
• Number of items: 1
• Dimensions: 9.00" h x .90" w x 6.10" l, 1.11 pounds
• Binding: Paperback
• 432 pages

From the Back Cover

This may be the most revolutionary book you read this year

We all played games as children. Today, millions of us lose ourselves in massively multiplayer games like World of Warcraft, strategy games like League of Legends, and social media games like FarmVille. Games satisfy our need to interact, compete, and exercise our imagination. And they're fun.

What if your business offered those rewards to your customers?

Consider looking at your business—whatever it is—as if it were a game. Open this book, turn your imagination loose, and discover how fun can generate energy that boosts your bottom line.

Are you?

• A marketer who wants to find and keep customers?

• A product designer who wants to create a memorable customer experience?

• A website designer who wants to keep visitors coming back?

• An executive who wants to make customers happy and boost profits?

• A game designer who wants to create a better social game?

This book is for you!

About the Author

Jon Radoff is an entrepreneur who focuses on entertainment and social communities. He created one of the original commercial games on the Internet, Legends of Future Past, and founded a content management system that foreshadowed modern blog and wiki technology. His newest startup, Disruptor Beam, is a social game publisher.

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