laptak2003/AmazonDataScience huggingface dataset:
Summary: Overall the book retains a lot of the same flavor as "Naked Economics" so it's very readable, interesting, and occasionally even funny. On the other hand, it's also a little more dry and less intuitive than its younger publication which may turn off some readers.Pros:-readable-very enjoyable experience overall-covers a wide variety of statistical concepts-provides lots of real-world examples to liven the book-makes attempts at humor that, while they don't always land perfectly, are appreciated for the good-natured attemptCons:-can be overly technical in its descriptions of concepts like standard deviation or correlation-not as much intuitive explanation. I felt I was left by the author to apply these concepts to the real world and found that off-putting as that is the entire purpose of the book-pacing is uneven. Sometimes you feel like you're moving along at a good pace and then suddenly stuck in concrete as a topic is beat to death for several pages.
Great book.  This should be mandatory reading for any Six Sigma certification program.  Specifically, the explanation of confidence intervals really demystifies the subject matter.  This guy's clearly a huge nerd.
I have a computer science background so I am quite familiar with at least the basics of statistics and data interpretation. And yet, reading this book, with its real-world examples and short case studies, has allowed me to see statistics from angles I hadn't known about and as a tool with significantly more applicability than I'd thought previously. In a world awash with data, a working knowledge of statistics is essential for people to make sense of it all and also to not be fooled by those who manipulate it to fit their world view. This book is easily the best (re)introduction to this science that I've seen and I'd recommend it to anyone who doesn't want to take 'facts' at their face-value.
I bought this for one of my college classes and enjoyed reading it. It is not difficult to understand and the author does a good job of telling stories and giving real world examples to capture the importance of statistics and ways to best present data.
I'd say Naked Statistics would be an OK college-freshman level book on applied statistics at a low-end school, but it lacks enough mathematical background.  Yes, I'm aware of Hawking's Law (every formula halves the sales of a book) but I think this book aims just a little bit low.How low?  Just a smudge....  maybe I'm just being a harsh grader here, but a *little* more math, maybe in a couple of appendices and it could have been an outstanding freshman book (and I say this with my apologies to Prof. Wheelan, maybe I *am* a harsh grader; he's a working teacher and I haven't taught in 20 years... )On the other-other hand, if you AREN'T a student, but DO want to get a totally painless introduction to statistics, then this book is about as good as I've ever seen.  In fact, it's not just totally painless, it's actually pleasurable (the examples in the book are often from real life and shed some real value outside of pure statistics).
The only reason why I gave this book a try is because Wheelan's other book, Naked Economics, was required reading for a previous microeconomics course. I excelled at that course because his writing style is really good at conveying relatively dry concepts into entertaining layman's terms. Same holds true for Naked Statistics. While I did well in my stats course without reading his book, it did a great job helping me concretize some concepts that I got tripped up over but needed to remember for my next stats course. Understanding the difference between t-tests, z-tests and p-values is like a no brainer after reading his book. Granted, he doesn't go super in-depth regarding some of those things but if you pair his book with your textbook, it'll help tie everything together. Some believe that a writing style has to be dry in order to be scholarly, but in my opinion, the better an expert can break down difficult concepts into common terms, the more of a master they are at their specialty.
If you've ever been to a hardware store or a building supplies store or, even, one of the online app stores (Google Play or Apple App Store etc) and found a tool or device that immediately made you think you could do a tricky job then you will appreciate this book. As soon as you read it you will think, "It makes complete sense that I could release federal election results early with a 68% confidence level and a higher margin of error! And raise that later to 99.7% confidence level wih a lower margin of error as soon as enough voting results have been counted."Be warned! After reading this book you may start to look critically at more and more of the data and opinion polls which come your way in media and news reports. Can't ask for more than this from a book!
Best book on explaining statistics, it's relevance and it's application, hands down. I have studied statistics as one of my core courses during my Masters, and I wish I had known about this book then. The examples and the explanation is impeccable and most importantly very intuitive. I wish there was a second part to this book which could go in details with advanced concepts with the same kind of intuitive explanation and examples. If there is, please please do let me know.
Highly recommended! What a great intro to statistics. I have a bachelors degree in economics, so I learned all of this before. 5 years since graduation though, I wanted a quick refresher in order to prepare myself for more advanced data science studying. This sure was a good pick for this purpose as the author made sure to provide intuition and translation into every day language and scenarios. However, I think these same reasons make it an excellent choice for anyone one taking statistics for the first time as a supplement to the more mathy, boring textbooks. This book fills in the space of confusion anyone faces when they, for example, see the regression equation for the first time. I wish I would have had it for my first statistics course
I have downloaded the Kindle version of this book, therefore regard my review with that in the back of your head.Wheelan makes Statistics accessible (and even, I dare say, interesting) through his style and narrative, but his book has a couple of shortcomings that I would have liked to have addressed - many of his examples are the "stock-standard" examples seemingly borrowed from other sources, I would have liked to see more recent or original examples being used. - referencing is difficult with his structure. I will not easily be able to get to the formulae and principles with the format of the book. To read the book from cover to cover is apparently the best way to approach it. - shortcomings to statistical methods are touched on, but not really discussed in sufficient depth. I will not hold this against Wheelan, since very few books on statistics do this sufficiently
I purchased this book based on the reviews and recommendation. To my surprise, this is more of words and letters than graphs and pictorial view of statistical concepts. I could not get hooked or engaged to the topic during the reading.
This is a well written book and the author does a great job of explaining statistical sampling and analysis in a straightforward manner. The analogies tend to be somewhat clumsy but also something everyone can easily grasp. The math is in the back of the book if you're interested in that part
This book is absolutely fantastic. I read a lot, and this book captivates you from the moment you pick it up. Wheelan is such a great talent in describing the complex, and delving the material into something for the common person to understand. I just had to write this review after I finished chapter 4. I have difficulties with maths, and his explanations just seem so natural, and thorough. This book allows me to really understand the equations and materials. GREAT READ THAT YOU CANNOT PUT DOWN!!!
I have two business degrees, BA and MBA, and I find this book to be a nice refresher of the main take-a-ways from my statistics coursework.  I do not work with statistics very day, so I desired to read something that would keep the topic before me in a way that feels relevant but not too "text book-y."  This book fits this bill nicely, and I enjoyed the bit of humor the author had the kindness to include!  :)  Nice overview of this very relevant topic.  I highly recommend it.
Would never have chosen this book on my own, but had to read it for a college class.  Some good points, some bad, Writing was ok and not too boring.  Again, not my style of reading material, but it worked for a class that I got a 4.0!
This book is a great way to break from staring at the tables and equations you are learning in statistics and actually think about why you are doing it.  This book made stats fun for me!
Beautiful, explains the basic rationale of the discipline while presenting highly impactful examples of how it's applied in the real world.Is a very breezy read on the surface level, but you'd be missing out if you don't slow down and ponder over what the author's saying. Just because it's a popular attempt doesn't mean that it's not as respectful as say 'Statistics for Engineers and Scientists' by W.Navidi. Serious students can get a lot out of this book, so can lay readers.
This is a very good book that attempts (and mostly succeeds) to introduce complex concepts in an approachable way. A couple of minor complaints, in particular among them is a sometimes distracting effort to make examples absurdly humorous. Some may find that welcoming, but it often seemed contrived to the point of obfuscating the lesson to me. Overall, though, an accessible and informative view into powerful statistical tools and concepts.
A really great book to read... written very eloquently, it lets you understand the intuition behind many of the statistical processes and methods... the book is good for someone with a non statistics background and even better for someone who does have a statistics background
Great book to understand simple topics of Stats on a deeper level. Example based and surprisingly funny. I really enjoyed Charles Wheelan's unorthodox approach to this subject. I will be looking to read more of Wheelan's material in the future.
Flipped through the book, does have some key points. It is helpful.
This book does an exceptionally good job of explaining mathematical concepts through stories and examples. The author does a great job at introducing simple concepts such as probability, then building up towards more advanced concepts such as regression. A highly enjoyable and educational read, even for someone with a math degree like myself.
If you literally have no idea about any of this stuff, it's well written an keeps stats relevant.  (I wish I had had him as my Stats prof at Dartmouth, rather than he who will not be named.)But if you know anything about stats, move on  It's a good book, but I have it two stars because I'm concerned that those of us who need and want it aren't going to be the ones who buy it.
The real life situations were entertaining and enlightening. My purpose in getting the book was to see if I could give it to my son who is an undergraduate and perhaps a bit apprehensive about statistics. I think he will appreciate the brush up against real statistics with examples that (in some cases) he can relate to. The book also was entertaining to me and informative too. My experience with stats goes back a half century to when (in grade school)  I recalculated batting averages  for Ted Williams each morning when the paper arrived. Never tangled with statistics after that. Never thought one could make a living doing regression analysis of team and player performance.Sorta wish there were more stories...  an index of additional cases even though  they are not wound into the story. Perhaps give each of them a rating for how outrageous the cases were: a 1-5 point iNullo award for incorrectly rejecting the null hypothesis.
In the last few months, I have been pouring over several books on data science and business intelligence and watching several related videos to get up to speed. The purpose was to get up to speed for a post graduate program in data science and business intelligence that I had enrolled for.First day of the program, first class / session (after the orientation, etc) was statistics... My head was spinning and I had lost all hopes on my journey in data science :) So many new jargons, so many new techniques which I could only partially understand or relate to! (Mind that I have always very good in mathematics and loved it)And then I came across this book "Naked Statistics" and am partially through it... Wow! The author seemed to have been through what I do now! And what a great relief that I could relate, comprehend and correlate now statistics to a "better" extend. Hopefully, it will be a "greater" extent when I finish the book.I was so overjoyed that I could not wait until I finished the book to create the review. Hope this review helps folks like me.
Charles Wheelan's Naked Statistics is an overview of the most important tools of statistical analysis: descriptive statistics, inference, regression, etc. The book is proudly devoid of formulas, although it does refer the reader to more advanced texts where applicable. Wheelan makes good use of metaphors and analogies in explaining statistical concepts; almost anyone will find his descriptions accessible.Where the book really shines, in my opinion, is in its discussions of the applications and limitations of statistics. Wheelan is not shy about defining the boundaries of conclusions reached via statistical analysis, and I agree with his basic premise that understanding how far statistics can take us is just as critical as understanding how to use it. "With great power comes great responsibility!"
For statistical novices, this book will give you a basic introduction to the most important statistic concepts, which are increasingly  relevant across domains and applications. It will expose you to topics that would be covered in three or more separate college level courses. As a recent Engineering graduate, I found myself wishing that I had read some chapters before I taken courses on these subjects, because I would have understood that material more quickly.For those with a strong understanding of statistics, this book will give you strong examples and illustrations to draw upon so that you can better communicate statistical concepts to others, especially those who don't respond well to math.This book goes a step beyond Huff's How to Lie With Statistics. Its worth the additional effort to pursue the deeper understanding that this book provides.
A great intro to statistics for those who are newer, and a great refresher for those more experienced. Many concepts explained intuitively all in one easy to understand book. Very entertaining and informative.
This is a kind of "Statistics for Dummies", almost stripped of any math or rigorous definitions. Mr. Wheelan, though, seems to be a born teacher, with a rare gift to find and unravel examples that will illustrate concepts in a rather didactic way. I think that even someone with some formal education in the field will thus find the text enlightening.The book covers the basic concepts, ranging from descriptive statistics to program evaluation, going in-between through correlation, basic probability, inference, the Central Limit Theorem etc. Topics are presented as a logic crescendo of dependent ideas that works very well.The author is always concerned in explaining the cares that must be taken â€’ and the traps to be avoided â€’ to obtain meaningful conclusions from statistical analysis. And, not the least, how statistics misuse can be employed to deceive.If you have any interest in the topic, Naked Statistics is a must-read.
Yeah, you read the headline right! This book will not help you clear any interviews or exam without the help of other books but one excellent thing about this book is that it will make you feel confident that you can master stats core concepts no matter where you are in your stats journey. A very good intro book for intro to Stats, must read for true beginner.Skip it if you are already strong in basic Stats!
Most people are not born with a love to learn statistics. It takes some motivation. This book is that motivation. I enjoyed every page of this book and I only wish I had read it years ago when I was in college. I would have gotten a better grade in it - hell - I might have majored in it....it's that good.
It is a good, entertaining read but since I have a little bit of statistics background I found it a bit basic. Statistical concepts are explained very well.
Worth reading.  He tries very hard to make statistics less dry, and to help one see why knowing some background, even if not any heavy math, is useful when reading news reports and so on.  Helpful background for reading or listening to analysis of different kinds - political, environmental, and when friends seem so sure of something but it doesn't make sense.
I read this book just for fun.  It was interesting and a good challenge when attempting to FULLY follow his math.  I was a math major in college, but NOT a genius math person by any stretch of the imagination.  Enjoyed the book.  He writes in a humorous and informative way, and he kept my attention through the entire book, which is a rarity when it comes to these kinds of books.
Great book. Very nice introduction to statistics, even for non-math folks. I took stats about 30 years a go in graduate school and wanted a basic tune-up as I begin to get back into it so I can explore "big data." This book is well written and gives very clear, understandable descriptions of the most important concepts.And I just enjoyed reading it.
This is a great book for those who have one or more statistics courses under their belt but rarely need to use the knowledge they may have gained.  Good refresher on the basics and put in terms that are readily understandable at any level.  Accomplishes what any good book does by putting the points it is trying to make/teach into a form easily grasped through with real world examples.  Have recommended this to several people as a book that serves as a refresher for fundamentals and a refreshing format that is a quick read.  Very much enjoyed this book and think it would be a valuable starting point for those who have a dread of perceived difficult subjects - like statistics.
This is an excellent resource to have handy when taking a stats class, no matter what level!
This is a fantastic book on what would at first glance seem to be a dull topic, but Whelan handles it so well you'll turn the pages like you are reading your favorite novel.  What is so amazing is how well  he explains the topic.  You might think of statistics the way they were introduced to you in school,  but this book is so clear it will jump from the page.
This was a great way to brush up on basic statistics concepts I had long since forgotten. It's an easy, fun read without losing any informational value. The content is presented in a way that's easy for anyone to understand; no need for advanced mathematics experience or recent education on the subject matter.
In the unfolding Age of Big Data, no one who hopes to understand the way the world works can afford to be ignorant of statistical methods. Not a day goes by that statistical analysis isn't behind some front-page story -- in politics, sports, business, or even entertainment. The statistical concepts of probability, sampling,  and statistical validity, once considered obscure and of interest only to geeks wearing pocket protectors, are now indispensable tools for the active citizen to grasp. Writing in a breezy and intimate style, with humor and lots asides to the reader, Charles Whelan attempts to unpack these concepts and explain them in English with a minimal use of advanced math, and he succeeds . . . up to a point.Naked Statistics was published just four months after Nate Silver's best-selling book, The Signal and the Noise, which covers much the same ground in a very different way. Whelan focuses on the nitty-gritty of statistical methodology, delving into such topics as how samples are chosen, what's meant by terms such as correlation, standard deviation, and regression analysis, and how to determine whether the results of a test are statistically valid. However, he doesn't lose sight of practical questions, unpacking such seemingly puzzling statements as "the average income in America is not equal to the income of the average American" and spotlighting the difference between precision and accuracy. Silver instead explains how statistical methods are applied in a wide range of activities, from baseball and basketball to Wall Street. Whelan includes lots of formulas laden with Greek letters, though, conveniently, they're confined for the most part to Appendixes that follow many of the book's chapters and can be skipped by a non-technical reader. (I ignored them.) Silver's book is refreshingly devoid of Greek letters.As Whelan makes clear, perhaps unintentionally, statistics is a forbiddingly technical field. Truth to tell, if you really want to understand statistical methodology and how it can be applied, you need a fair grounding in mathematics and a tolerance for terminology that doesn't appear in everyday English. In fact, you probably need to take the same sort of graduate school courses Whelan took years ago. This is heady stuff!All in all, for a run-of-the-mill mathematical illiterate such as me, Nate Silver did a much better job getting across the significance of statistics and how its methods are applied to strip away the complexities of today's often baffling, data-driven world.
I was interested in learning something about statistics without trying to go through textbook presentations.  This book does that extremely well:  It conveys the basic concepts used in statistics without getting too deep into the underlying math.  Examples are good and (for statistics) reasonably intuitive.  Written in a breezy manner (occasionally a bit too flippant for my taste) and well organized.  I expect it would work well as a supplemental text for an introductory statistics course.  In any event, it was spot on for the general reader who wants to get smarter about the subject.
Not quite as great as his other book, "Naked Economics". However it was still a pretty decent read. I never had much experience with statistics, and I definitely feel like I did learn quite a bit from this book. A lot of the information also passed over me, but I am preparing for a second read-through. Great intro for beginners in to stats, and definitely entertaining to read.He tried not to get too much into the math, but at times it was unavoidable. I thought it was balanced pretty well though
If you are a high school/college student entering their first stats course with fear and trembling or just someone who wants to get an idea what statistics is all about this is the book for you. Wheelan doesn't burden his texts with a lot of equations, but rather tries to give you the intuitive sense behind statistical key concepts. It is a great place to start or get a quick refresher. The author is lively and engaging with examples that are sometimes imaginary and fun, or from the real world and relevant. This is the book I thought I was going to get when I read Nate silver's "The Signal and the Noise." That's a book that shows you what statistics can and cannot do, this one shows you why and how.
This book is good intro to stats book that it condensed complicated statistics concepts into easier to understand ones. There are no complicated formulas, and the author used everyday related examples to help readers understand. However, this is by no means an advanced stats book. Don't expect to see anything beyond t-tests and confidence intervals. You probably shouldn't substitute your text book with this either.
Used this book to teach introductory statistics at the undergraduate level. This was helpful to give students examples that would resonate with everyday life. It supplemented a textbook, and was a nice compliment. The students who read it seemed to really like it.
This book is both a good introduction to practical statistics and an entertaining read.  I use the statistical analysis methods of this book on a daily basis, and yet this book provided a number of excellent practical logical explanations of these methods that were new to me.  I think most readers with technological or scientific interests will enjoy this book.
This book finally made sense out of stats! Wow! Thee best book on intro stats hands down!
An admittedly nerdy book, but the author presents the info in an often funny and easy to digest manner without getting caught up in too much technical detail. Great read as a refresher or primer for an upcoming class in statistics.
It drones on, and is difficult to stick with for extended stretches, but this may be the nature of the beast (topic).  Content is excellent, but my brain needs some synthesis scattered in every so often amidst the dozens upon dozens of examples/narratives/stories of "real-life" statistics.  Otherwise, I find myself musing "what were we talking about again?" Such an important main-subject of our our times (with offshoot topics of: big data, analytics, data mining, hyper-targeted marketing, privacy degradation, as well as the inevitable slide towards orwellianism as the logical extreme result of complete command of the data: over-surveillance, misinformation, propaganda, denial and/or manipulation of truth, etc.), and this book is an important contributor.  Writing tone is excellent with rare and proper self-depricating style, as if the author knows the topic is more important than the author.  This can be a unique combination.  Well worth the read.  Kris Keeney
Purchased this book as a requirement for a university philosophy class. I am not completely done reading it, but I am enjoying it very much. Easy to read and understand. Great for anyone and everyone to read.
I'm only about a half way through the book but I must say this is the easiest to understand and most entertaining book on Statistics you're going to find.  Five stars.
As a professional student, with almost 30 years of college under my belt, I can say that statistics courses are, on average (!), the worst taught classes.  My hypothesis is that people who excel at statistics think differently and, therefore, teach from a different perspective than those of us who didn't 'get' statistics right away.Wheelan's book was very easy to understand, with lots of descriptions, and not laden down with algebra or calculus.  If you are finishing your PhD in stats and are considering teaching, you should buy this book just for the examples.  Your students will thank you.
I love this book.This book is for beginners in the field. It well organized with many examples, intuition explanations and without math proofs and code examples
I am very pleased with the presentation of material in this book.  Currently I am reading the review section on Linear Algebra and (having taken a course in the subject in the past) I have found many nice intuitions which were never presented in a more formal and comprehensive treatment.I am sure that I will continue to find such illuminating expositions on the remainder of the topics in this book.I am looking forward to the class next semester at SBU taught by the author which I am enrolled in.
The analogies presented by Skiena help the reader grasp the bigger picture and be able to understand the purpose of many difficult topics.
Naked Economics is an awesome 5 star book.  This is close to that, but a little more repetitive and mundane; but for a Stats book, it rocks!  Naked Money is also good-- love hti sauthor-- wish I had these when I was in college and so grateful to have a refresher that is entertaining now.
The author gives a complete big picture of what statistics is and what it is used for. After reading this book, you will better understand the usefulness and pitfalls of this powerful math tool. The examples are very clear and easy to follow. He does not use equations as examples. Charles Wheelan uses everyday examples to make his points. Excellent book for people who want to understand the reason why statistics are such a powerful tool without having to go through all of the math involved.
In my profession in the financial field I stay on the lookout for books that may make it easier to explain some of the concepts I use to the clients I work with so picked this one up to see how it handled statistical analysis and regression. I had long been a fan of the classic "How to Lie With Statistics" by Darrell Huff written in the 50's and this book is "an homage" to that work. I enjoyed it because I like statistics and I think the average reader will enjoy it but they may want to shy away from the chapter appendixes as they get more in depth. The author does a good job of steering away from the more complex issues (non-linear regression analysis, for example) and comes up with some good examples to illustrate his points. He does one of the best jobs I have encountered of explaining the "Monty Hall problem" which is why an individual, after having picked say, "door number one" and Monty shows that door number 3 has a goat behind it and offers to let the contestant change his mind to door number 2. It sounds counter intuitive but the right choice is to make the change. Why? Guess you'll have to get the book and check it out.I liked his explanation of concepts enough that I purchased his book "Naked Economics" despite my extensive study of the topic in anticipation that I will find some nuggets of explanation that I can use.
I read this book for a research methods class and I honestly couldn't have asked for a better explanation of statistics. The author, Charles Wheelan, explains in the introduction that he struggled with learning statistics and other economic-related subjects because he couldn't see how it applied to the real world so he fills the book with examples that we can actually relate to in our everyday lives. For example, one of the chapter subtitles is "How does Netflix know what movies I like?" I'm pretty sure every Netflix subscriber has wondered that at least once while browsing through their recommendations. In addition, Wheeler is actually an amusing writer and I found myself chuckling more than once while reading this.I was very surprised to have found the book as interesting as I did. Math was probably my least favorite subject in school and, in general, I find the entire subject a bit boring. However, this book really made me interested in how statistics play a role in our everyday lives. I highly recommend it to absolutely everyone. You don't need to be taking a class or work with statistics to find this book interesting.
Easy to read and makes statistics easier to relate to!  This author is great!
I'm not a statistician. In fact, most of my understanding of statistics stems from probability as an application to Machine Learning. That being said, this book helped me feel a bit more confident in understanding statistics.Wheelan does a good job of giving overviews of various statistical concepts with a lot of examples and a bit of humor. At times, it felt a bit too hand-wavey when I would have enjoyed some more details, but that's not really the intent of the book.It's a great book to get the overview of some basic statistical concepts and an entertaining read (for a stats book).
Naked Statistics is very well done. This book gives you an entry look into the world of statistics. If you have ever been curious about how statistics work, and never took a class, this book would be good for you. Charles Wheelan talks about what statistics does and what it looks at, but doesnâ€™t get in to how it works. He really simplifies the topic to make it easy for anyone to understand.The book is written from a perspective that the audience hates statistics and has never wanted to look into it at all. Wheelan does a great job in addressing that, and he tries to make the process less painful. His examples are off the wall and make reading the book entertaining.This book doesnâ€™t really teach you statistics, but tries to peak your curiosity, so you do continue on your learning journey. He doesnâ€™t go into all of the pesky details of why the math works, but he does have appendixes and sources of where he gathers all of his sources for each section of statistics he goes over.I really liked how Wheelan explained how different groups can mess with data depending on how it is interpreted or how people can skew the methodology to produce certain results.  He has a great explanation of how people lie with statistics or distort confidence in results.
I read this book. I enjoyed this book. I can't remember anything from this book. I remember the overarching narrative, but I can't recall a single interesting story or narrative from within.
Awesome book. Great refresher or introduction to stats. Author approaches everything very intuitively through accessible examples and then introduces the math behind the concepts. Typically the opposite of how a classroom functions. The structure made for a very enjoyable book and made the subject easy to learn.
This book is a required text for a Media Management course at North Seattle Community College this spring. I bought it because the wait time at King County Libraries stretches into months... It's readable, the examples appeal to both genders, and the doubters in the class (a majority) have been won over. I would recommend this for either anyone who wants to understandand actually use statistics for any reason, or for a book club that wants a good laugh and lots to talk about.
The book is very example oriented and has code snippets. About 4 pages had blurry print. You might need to install pycharm or Jupiter notebook to quickly try reinforcements of knowledge gained.
Everything written in this book bodes well,unquestionably  a decent read!prescribe  this book and would peruse more books from this writer.many thanks to the author for giving us such a beautiful book.
Complete guide to learning data science. All information described in detail special for beginners. If you want to know all about data science from this book for you.
when applied, it looks different to each person, business, or organization utilizing it. While the term may not be easy to define
Very important bood and informative book.this book is really amazing. This book is definitely recommended.
Did the author attain permission to use this information from the author that originally wrote it?
A lot of ink has been spilled over the past few years on the subject of data science, but this is the first book I've seen that goes directly to the top data science practitioners in the field to find out what they do, how they view the industry and how they got to where they are.I thoroughly enjoyed the authors' first book (120 Data Science Interview Questions), and this second effort is equally informative.  If you have any interest in learning more about what this rare beast, the data scientist, is, then this book is a great place to start.
Really good.  Not a handbook per say, but a collection of interviews with leading data scientists.  Similar to the book 'Data Scientists at Work' (also a collection of interviews), which I also read, but this is way better.  Useful for inspiration/meta thoughts on data science, not really a how to ('handbook' is kind of misleading).  Probably useful to people with some idea of what data science is, might not be as useful for those who know nothing about the field.
This book is a collection of stories shared by top data scientists from many fields. Definitely a good read, especially for those interested in what goes on "behind the scenes" in the very diverse field of data science.
Great collection of interviews for those who are interested on where the data science industry has come from, currently is and where it is going. Whether you are curious as to what the industry is about or determining your next career move, this read is a must! I highly recommend to others.
It's always great to hear directly from the masters. The Data Science Handbook provides exactly this opportunity.This collection of interviews was so good it made me wish that it was a series. I would love to read a sequel with another 20 data scientists.p.s. I also received a free copy of the book in exchange for posting this honest review. I had written it up before the authors got in touch, so this is an unbiased review. They simply asked me to post it to Amazon.
Book does not go in depth.There were many useless information.Poorly written.
The Data Science Handbook gathers 25 interviews of Data Scientists. Interviews are well done, most questions depending on the previous answer. This gives a nice feeling of discussion between the interviewer and the Data Scientist. On the content side, it provides interesting insights about the job of Data Scientist. The book is however biased towards pioneers in the field spending 14h a day working, which is definitely not representative of the overall Data Scientist population.The 25 interviews are covering all major Data Science topics, including data preparation, automation, Big Data, the role of the Data Scientist and moving from academy to industry. Although some of the selected Data Scientists are clearly well known (DJ Patil, Hilary Mason, etc.), others are quite new to the field. It looks like they have been interviewed because they knew the editors or work for a â€œtrendyâ€ company. I would have rather chosen to include other key Data Scientists such as Dean Abbott, John Elder, Eric Siegel and Gregory Piatetsky-Shapiro. The book still remains a great source of inspiration for experienced Data Scientists.
Great for any data scientists! Very insightful and intriguing book!
Awesome insights about being a data scientist
This book was not really what I was expecting.
I have a somewhat different take on this book than the other two reviews posted to date.  However, I've read them both, and they're legitimately laudatory, so please read on.I posted a brief review on Quora.com -- where I first read about the book -- as follows:"Interesting reading.  I was expecting/hoping for a little more in the way of case studies, food for thought about conceptualization of data requirements and use of big data, etc.  However, if you have an entrepreneurial bent or are interested in understanding more about how some of the number wizards look at industry uses of data, it's worth a read."To amplify on this take, I'd like to make it clear that I approached it from a general reader's perspective... as a potential user of big data and as someone looking to learn more about how to make the leap from owning a bucketful of information to turning it into real knowledge.  That kind of work is still needed; this isn't it.  The worlds of data science and customers of the fruits of data science still are pretty widely separated.That said, this book appears to be an excellent atlas to the specialty and the solid guide to the best route toward formation of data science practitioners (although definitely outside my experience enough that at least a good chunk of its wisdom probably was lost on me).  I also got a sense that it offers insights that might help data scientists become better at reaching out to potential users of their services, which also would be a positive.So, for those in the target audience, possessing at least some of the basic quantitative and analytic skills the field requires, I'd unequivocally endorse this book.  For others (like me), it can serve as a means of understanding at least some of the skill set that can be expected of data science practitioners.  However, it's a lot tougher read without at least some background in the area, and I have a strong sense that I didn't get everything out of it that was there for data science cognoscenti.
I am new to the field of Analytics/Data Science. This book has given me some invaluable advice as to how to reach my goal of becoming a data scientist. If I can accomplish at least 50% of what these top-notch data scientists have accomplished, in the next 4-5 years, I'd consider that to be a great achievement. They have shown me the direction and now it's my turn to make it happen.Top takeaways:1. Steep learning curve2. Math's the crux3. Opportunities abound in DS4. Industry's better than academiaThank you, guys. This book is worth every cent of the 20 dollars I paid :)
I'm a software engineer working in machine learning. I guess you could call that data science. I expected a book of case studies, refined techniques, and insights I could use in my own work. Instead I got this substanceless fluff, a huge collection of softball interview questions ("What do you do? How did you get where you are? Where are you going?"), and an unpleasant sampling of startup culture. When the second interviewee in a row strongly recommended cutting back on sleep in order to get more work done, I skimmed through the rest of it and threw it out in disgust.
As a practicing data scientist these interviews are a great read - they provide insight into how other data scientists got to where they are, go about their daily tasks and think about the future "data science".  Interview questions are well crafted. It's an informative read for people of all levels in data science - from those just starting out to those leading large teams at established companies.  Some of the interview veer off of data science proper, such as John Foreman's discussion of working at a private company vs. a startup trying to go public, but maintain interest for anyone in the field.
Very easy to consume because written as a story
Just few examples:"I decided to go with a case study for this book, let me explain why in 10 pages". Man, I don't care about best practices to write a data science book, don't waste my time with explaining your editorial choices!"Detailed, careful explaining why it helps to download data from the public web-server and upload it to Google Cloud in terms of cost ("you know, it's zero cost of storing data at where they are") and performance (Google Cloud internal networks appears to be faster than public internet, so it really makes sense to download them and upload again!). Wow, amazing, no way I would guess it before buying a book!Is it a book for a Kindergarten?Couldn't struggle further than 2 chapters, tremendously annoying. Maybe somewhere after real talk begins, I just decided to refund.Maybe, just maybe, it fits thought the needs of those who have no idea about data science whatsoever.
I learned a fair amount from this book and ended up implementing production systems based on it. It could have used better editing, but it will still teach you a fair amount.Biggest praise: It shows you how many different Google Cloud components can interconnect to build a full machine learning pipeline, including lesser-known but important things like Dataflow, Dataproc, and Cloud AI Platform.Biggest criticism: It spends much of the book building toward Chapter 9 where it wants to show you how to use Cloud AI Platform. However, that chapter is harder to follow if you're coding yourself than previous chapters were. It lacks needed explanations of various bits of code, and as of my writing the code doesn't work. I think that it may be fixed by the time Cloud AI Platform is upgraded to support TensorFlow 2, so you might not run into this problem. Another criticism is that so many corrections were applied after the fact in GitHub that certain parts diverge significantly from the book, making it harder to follow.Criticism aside, you will learn a variety of different technologies in GCP that you can put to use. It helped me get a sense for the "big picture" of data pipeline development on GCP, and gave me some exposure to Spark and Cloud Dataflow on GCP. This may well be the best book for you if you want to understand data engineering on GCP specifically.One warning is that I wouldn't recommend skipping chapters. Instructions and code are technically provided for that in GitHub, but it won't necessarily work 100% correctly and various chapters refer back to previous chapters. You should expect to spend a long time with this book going cover to cover, but you will learn a fair amount in the process.
Wow. A true tour of data science and engineering on the cloud.It's been a few years since I've worked with tools in this field, but this book was a clear level-headed view for data engineers looking to derive and drive insights from data. Using a core example use case and following it end to end through the entire book (and indeed cloud tools integrated with each other) helped me keep track of what was going on, and kept things from becoming a book on theory rather than one of accomplishment and answers. The purpose and process for each tool was clear, and I also appreciated the explanations of trade-offs and the value added for the choices made. The practice of data science is a LOT easier now with cloud/serverless tools than eight or nine years ago, and I feel this brought me back to the state of the art.
While Lakâ€™s conversational style can be a turn off to some who just want an answer and donâ€™t care about how, I liked this book. Many times with books like this you get an answer or a recipe and youâ€™re done. What happens when your answer or recipe isnâ€™t right for the situation? Iâ€™m glad Lak explains his rationale and letâ€™s it be known that thereâ€™s more than one way to do it. Could the book have been condensed without the explanations? Yes. Would it have been like almost every other book in the space? Yes. Check out this book if you want a well thought out answer and maybe alternates. If you just want the â€œright answerâ€, then buy something else.
I knew this book for me just a few pages into the first chapter.  This book by Lake is unlike many other books of data science and particular technology that just enumerate the how-to's of the particular technology.  Lak starts with a concrete user problem strongly anchored in probabilistic outcomes, and then steps through a typical data science process of discovery, refinement, and then converting to a production pipeline.  While teaching about GCP technologies along the way, the book stays strongly anchored in the original user-problem.  There is not a corner of GCP that is needed for a full production data science product that goes untouched in this book.  The material is well covered, with pointers to deeper material and user manuals.I received the first edition.  As GCP technology evolved, Lak was posting updates to his blog on Medium so that everyone could take understand the updates to GCP and how to use them.  I was pleasantly surprised by getting these updates and made having the book that much more valuable.
Narrative structure in a technical book is hard to find, and this was executed last masterfully, with lots of code examples for you to follow along with on your own. Highly recommended.
The book is easy to follow with detailed descriptions of each step followed to build a project from start to end on the Google Cloud Platform.The book is also accompanied by a code repository which lets the readers try out the project themselves.Strongly recommended for data scientists learning to use the platform.
Wonderful book filled with great examples and very engaging writing style!  I particularly appreciated how realistic the examples are and was able to use many of the code examples to bootstrap my own projects.
This book was a sad disappointment. The author goes on and on, in long sentences, on unrelated statements instead of addressing the fundamentals of GCP. A waste of time and money. The incentives for publishers to release catchy titles and bloated electronic content on high-priced tags are clear: profits by deception.
Really nice, good price
Excellent book for learning which GCP services can be used for what portions of data analytic pipelines. From data acquisition all the way to model revalidation.
Very interesting and well written
I honestly felt like I had been swindled out of 12 bucks.
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