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This book surprised me as it is not a survey of the ABCs of Buddhism which so a lot of intros test to provide yet often fall flat while doing so. Rather, this is a look at the very heart of Buddhism through some of the Dalai Lama's favorite teachings and texts. I think someone fresh to the topic will have so much more of a *feeling* about how Buddhism can transform the mind in such a positive and attractive e four noble truths here come alive, not a flat depressing list but as a framework where things like karma and "dependent arising" come into focus in a very clear way. The next section, on one of the amazing short texts on training to generate the "mind of enlightenment" and the insight that sees what reality really is, is one of my favorite teachings. And the final section is based on Atisha's work that illustrates the essential points and stages of attaining Buddhahood.I have read lots on these subjects before, but somehow the clarity of this presentation really hit s was also nice to have a book that I could obtain through in a weekend.

I have taught this course for a lot of years from different texts. I picked this text this year because it seemed concise and I liked the problems, which seemed important. However, the homework in Chapter 2 (on sequences, the first non-review chapter) is causing serious difficulties I did not anticipate. In math, theorems are proved using prior results. The results are stated in a certain so that the important prior results are available when the theorem is stated and proved. This text sometimes violates that traditional organization and often confuses the students about the of the results. In a lot of texts you can use the theorems in the current section to prove that section's homework. But, in this one, there are issues which request proofs of of results without being clear that those results are steps toward the proof of, say, Theorem X, and you are not supposed to cite Theorem X or higher-numbered effect to prove those steps. The of results is unclear--not just once, but often. Usually there is nothing in the homework issue that indicates where it belongs in the and which theorem it is proving. Why not cross-index them? Theorem 2-9 needs theorems from two sections later in to be proved, and it is only in the homework. When the steps are requested in the homework two sections later, it is very hard to be sure which results were "prior." The students are confused, and it makes marking homework much harder because I have to pause to explain that the effect in the text the student used was not actually prior to the effect we are proving. Some major results, such as "Cauchy sequences converge," are stated but not proved in the text. The proof is left to the homework with some key stages described only in the homework. But this necessary proof is clever enough that I think students should see it done well by the author. Leaving it to students means some will never figure out how it works (some won't even be assigned those problems). The necessary homework issues that caused me to pick the text are too numerous; the exposition is missing too much. I know from experience that the students cannot fill in those gaps by themselves, so I am needing to cover too much in class. A text at this level will always have a lot of results the instructor needs to clarify. That is a given. However, some necessary results could have been stated in the exposition with a comment that the proof is issue X, rather than entirely omitting reference to the fact that the statement in issue X is an necessary thought in the flow of the results. Maybe later chapters are better organized, but I will look for a various text next year in spite of its desirable conciseness.

I can't recommend this enough. I've been studying and practicing for decades, and His Holiness cuts through obscurations with the finest knife. This is not an simple read. Each sentence is very dense and powerful, and each requires reading, rereading, and meditation. The amazing clarity that results from reading His Holiness' teachings, however, is beyond value.

My teenage son wanted to discover Buddhism, a path I followed for a lot of years, and asked me to recommend some core Buddhist texts. Instead of going directly to classic Tibetan Buddhist spiritual works in translation, I decided on this Introduction by H.H. the Dalai Lama. It's not too long, which is amazing for someone who wants to check out this path without committing to a large tome, and it's definitely not dry. It covers the basics in a conversational style, but also contains a discussion (with excerpts) of some classic Buddhist texts that give my son a taste of what Buddhist literature is like. A amazing put to begin for an overview of Tibetan Buddhism.

I should preface by saying that I'm an undergrad and so far have used this book in a first quarter of true analysis. So please take this review with a grain of salt. I will modernize it as we go along the book in class.Overall this is a amazing book with challenging problems. I think the author did a amazing job giving the most primary definitions and building the proofs on those definitions. Of course, more definitions are added as you go along. He also goes deeper into the material than other books. For instance, other books on true analysis state the Bolzano Weierstrass theorem for sequences. That is, every bounded sequence includes a convergent subsequence. Kirkwood, on the other hand, first proves that every bounded set has at least one limit point, and then proves that every bounded sequence has a convergent subsequence. I think that this kind of approach gives a beginner in the topic a broader and better understanding of it. Another example would be his definition of closed sets. He defines a closed set as a set whose complement is open. Other books I've seen define a closed set as a set that includes its limit points. The latter is proved in Kirkwood as a corollary. Again, it's the idea of starting with primary definitions or theorems of a certain concept, and then developing "sharper" or more focused theorems out of it. I like this rkwood also doesn't hide the theorems and ideas in the problems. For instance, I saw some books (two, so far) that introduce lim sup and lim inf in the issue sections. The only theorem that I saw hidden in the issue section was the Cauchy-Schwarz identity, but this one comes up so a lot of times in mathematics that you're bound to run into soon and prove it.Having said that, I don't think this is the book for self studying, although for that matter, I think that if true analysis is someone's first encounter with higher mathematics, then they should take a class in it. I'll elaborate on why this isn't a amazing book for self studying: First, the proofs can be a small too succinct. There are gaps for the reader to fill in, and those gaps aren't always acknowledged by the author (i.e. no "this should be filled in by the reader"). This means that anyone reading this book needs to go carefully through the theorems and reason out why this one thing works or why it concludes the proof. Besides this, the burden of explaining "why do we need to go through true analysis?" seems to be left to someone who's more versed in mathematics, i.e. a mathematician teaching the class. Of course, if you like math then you like true analysis for its beautify and the fun in solving problems. You also know that the theorems and definitions in the book are required to solve the issues at the end of every section. In addition to that, the examples in the book aren't provided to support in solving the homework problems. They're usually there to support solidify the understanding of a concept. Most examples are in the vein of "The sequence {a_n} = {1,2,3,...} diverges to infinity". This isn't going to support you prove any of the issues at the end of the section. Also, some of the issues can be too difficult for students to solve on their own. The proof of the uncountability of the reals is left as an exercise. You must either be Cantor or very talented and creative to figure out a proof for that on your own. However, you also shouldn't skip it, because it is very important. There must be someone who could either tell you how to do it or give you some tips on how to do it. Lastly, there are some errors in the book that would go undetected by a student and would only confuse him or her. Again, this is a put where the assistance of a professor is needed. However, this isn't to say that the book is riddled with errors. In the first three chapters I only found two errors (with the assistance of my professor) - one was in the statement of a theorem, and the other was in a tip at the back of the book.

This is the first book in the "A Very Short Introduction" series I have read. Slightly larger than seven inches by four inches, and a bit over 100 pages long, they are diminutive books for sure. This one on relativity, I found very interesting. Relativity is a subject I have always had difficulty wrapping my head around but Stannard does a beautiful amazing job of making the topic sink e book is divided into two sections. In the first he covers unique relativity, and, in the second, he covers general relativity. In the preface, he mentions some ideas about space, time, and matter that we might take for granted in our Newtonian world. In the first section he redefines five common sense ideas: we are all in the same three-dimensional space, time passes the same for everyone, the idea of simultaneity, there is no speed limit, and matter is conserved - it can neither be made nor destroyed. In addressing these topics, Stannard delves into time dilation, length contraction, the twin paradox, loss of simultaneity, space-time diagrams, four dimensionality, and the ultimate speed of the universe - whew! All interesting items for sure. I particularly enjoyed the section on the twin paradox - and Stannard's clear explanation - where one twin travels to another far away planet and back at near the speed of light, only to search that the other twin has aged te that Stannard does use some formulas to demonstrate the concepts, but don't worry, if you have a primary background in algebra, it should all create sense to you. The formulas, I think, are important to convey a proper understanding of the material, but even if you are not up to par on your math, he does a amazing job of explaining the theory so you shouldn't have a issue here. He concludes with a discussion of different interstellar phenomena, such as quasars, pulsars, black holes, virtual particles, critical density, Hubble's law, and is book was well written in an explanatory fashion, so I think I will be checking some of the other titles in this series, of which there are many.

I recently read a handful of books on relativity, and I rank them as follows:Highly recommended introductory works: * Relativity Simply Explained by Martin Gardner -- best introductory book. * The Elegant Universe (chapters 2 & 3) by Brian Greene -- extremely lucid, but not as in-depth as Gardner's book -- possibly the best if you wish a shorter introduction. * Einstein by Walter Isaacson, chapter 6 (special relativity) & chapter 9 (general relativity) -- not just a amazing biography, also a very lucid explanation of Einstein's ideas. * The Fabric of the Cosmos (chapters 2 & 3) by Brian Greene -- a discussion of general relativity & the nature of spacetime.Further reading: * Inside Relativity by Mook & Vargish -- amazing introduction to Newton, along with amazing sections on what high-speed objects look like and a amazing section on how Maxwell's equations of electromagnetism relate to relativity. * Relativity Visualized by Lewis Carroll Epstein -- a amazing extra book to read, if you wish to delve more into truly understanding how it works. Not recommended as an introduction. * Relativity: A Very Short Introduction by Russell Stannard -- might be a amazing introduction, but not as lucid as some of the books above. * Relativity by Albert Einstein -- not recommended. It's amazing if you wish to see how Einstein explained it, but it is generally not a amazing introduction. Cumbersome, difficult, and is book has a amazing section on 4D spacetime and the "block universe". There was also an in depth description of why the geodesic is the path with the longest proper ere were some statements in this book that seemed rather confusing to me and possibly outright incorrect. There are some sections that are massive on equations. Although some might search this to be a amazing introduction, I think there are better books out there, and I can only recommend this book with some annard is British, so his writing style might not seem quite as comfortable for an American. This is a very minor issue, but I felt less engaged by his writing style than I did with a lot of of the other books listed above. On the other hand, British readers might prefer his book over an American's.Anyone interested in truly understanding relativity will likely wish to read several books, in to view it from multiple frames of reference.Enjoy your studies of this fascinating subject!cheers:)

A lot of years ago, Stannard was a tutor on my physics course and gave lectures on Unique Relativity. He was very good, with an obvious love of his topic and a genuine desire to communicate the ideas to 's quite surprising how a lot of physicists never go beyond the Unique theory to obtain a firm grasp of the General theory. Stannard is a notable turning to the topic a lot of years later, I naturally chose a book by him. And in any case, I'm gradually working my method through the entire VSI series.I really do think that this is the best book with which to begin if you wish to tackle Relativity, and an perfect refresher if you have already studied the subject. It clarified a lot of things for me and introduced a few completely fresh e math is fairly simple, certainly nothing beyond high school level, although the square root symbol written as a V had me puzzled for a e Amazon product description says the book has 144 pages. In fact it's 114, about par for this so, the Look Inside feature here will reveal some typos, like the '3/5 = 0.67' error on page 7, pointed out by another reviewer. In the copy I bought (from Amazon) these errors are corrected.[PeterReeve]

Russell Stannard's little book the reader a solid understanding of unique and general relativity. Having read more than 25 books on relativity, I recommend this book to everyone as their first primer in to obtain an accurate understanding of the fundamental principles. For example, the so-called twin paradox, which is incorrectly presented in far too a lot of books, is properly and elegantly explained by Stannard. Also his discussion on the curvature of spacetime is novel mind opening.

A very thorough and well written math level is about tenth grade and I still had no major difficulties with comprehending the authors explinations.I found this book so intersting,I have purchased math textbooks to improve my math so the book contains recomendations of other books to further discover the subject.

This book serves as a relatively amazing introduction to fiber optics. The book has a rather thorough derivation of the theoretical modes in waveguides and fibers for various index profiles, but is more weak on the experimental side e.g. scattering mechanisms for light is only discussed briefly. On the whole, the book can be recommended as an introduction, but probably not as a stand-alone reference. The by far biggest drawback of the book is the index or rather lack of index. Considering the huge amount of info presented in the book, the index is almost non-existent. This seriously impairs using the book as a reference handbook.

As a budding atmospheric physicist (entering graduate school this fall) holding a B.S. in mathematics and possessing decent knowledge in physics and chemistry, I was extremely disappointed when I bought this book for self study. Andrews summarily exposes the necessary topics, with most of them lacking in breadth, depth, clarity, and physical insight. Additionally, the tone is rather dispassionate. Fortunately I stumbled on 'Fundamentals of atmospheric physics' by Murry Salby, and search it a superior, lucid read. I'd highly recommend going for that instead.

Although I have done a significant amount of digital photography since digital cameras first hit the market, I search this ebook indispensable. The very best in clear and concise technical writing, well organized/edited. The excellent reference and tutorial to superior results. Filled with pictures, useful charts and such. A must for all seeking to learn photomicrography and for those who all ready skilled. This is the best ebook that I have ever owned.

I came across this book searching for amazing introductory texts to be used as companions in a bioinformatics course intended for an audience of graduate students in computer science at the University of Chicago. This is definitely an outstanding text for this purpose. It's genetic engineering in a nutshell. Each chapter is summarized at its end by a "concept-diagram" that connects all the essential info in that chapter (I want other authors could do the same with their books). The book is divided in eight chapters, spanning over 165 pages approximately. It covers primary molecular biology (gene organization, expression), manipulation of nucleic acids (labelling, hybridisation, electrophoresis, and sequencing), restriction, modifying, and joining enzymes, vector techniques, cloning, recombinants, and applied problems (making proteins, transgenics, etc).

This book is by far the best in the field of geometrical optics dealing with 3-d, 5-th and higher orders aberrations in symmetric optical system. The language is very clear and simple to follow, it is written for a broad audience. I would personally recommend it for all how has an interest in the theory of optical aberrations.

This book was my first "introduction to melody technology," and most of the info in it is still up-to-date. Obviously, some of the technology and computer will have been updated by now, but the general principles contained in this book are an invaluable resource for any melody engineer, singer/songwriter, or composer.

This is a nicely written book for beginners who wish to learn about data science. When I say beginners I mean a intelligent high school upperclassman. The writing is not mathematically challenging and the examples are simple to follow. That said, the content left me scratching my head. The issue was not that the writing was poor or the subjects were hard but rather I don't know why the authors included it. For example, early on the authors talk about binary representation. That is sorta-kinda useful but not as a core feature for a data scientist. Other oddities contain the coverage of the central limit theorem and law of huge numbers. I teach university level data science and biostatistics and I thought the explanation was nicely done but again I found myself thinking why are they taking the zone to cover this as the core part of a book on data science. There are a lot of interesting chapters (like the coverage of database connections and shiny) but so much of the material is barely an appetizer not even a light snack. While it is amazing to create beginners aware of things that can be done, the reader is only able to break the surface of some very deep e code is not poor but it could be better. The typesetting on the code blocks could use work. The huge font makes it simple to read but the method it wraps makes it rough to study and it causes it to not really conform to the famous R styles (like Google's). The choice of R packages is okay but it could be better. In particular, *many* data scientists work extensively with the tidyverse packages and they do data manipulation using dplyr. While bits of the tidyverse are presented it does not obtain enough attention and the lack of dplyr help is a very poor oversight. Basically the code looks closer to 2014/2015 then 2017/2018.If you are a reader starting from zero then this is not a poor but if you have any data manipulation experience begin with R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. It is superb and on the web.

This is definitely an intro book - it's not poorly written but also not the best on the uses R, which is an open-source, statistical - which is amazing - but R has some nuances that can be difficult to pick up, and those are not really covered here. As a practicing erstwhile data scientist, it's really hard to leave out statistics from the work (without fully understanding the data, the biases in the data collection and reporting, what's missing and what's an outlier: valid or not?) people can create some really misleading and wrong conclusions while exploring data in the name of "data science." So it would be amazing for some practical hints of how to approach fresh datasets for exploration, recognizing that not all datasets are going to be cleaned and curated for the data scientist. Having recently mentored a student who didn't know how to recode variables, that's a key component that should also be covered. It would improve also by following some of the O'Reilly format approaches for presenting code in a expect to dip toes into the water but this book is very solidly in the shallow end of data understanding, exploration, and data science.

There are a lot of books on the topic. However I like how topic is presented and explained. The books has nice discussion on material constitutive theories. If you wish a rigorous mathematical book on continuum mechanics, then this is not the best choice. But if you are at beginner or intermediate level, then this book may be valuable to you.

Till date I have not found a single best book for applications of statistics and probability to healthcare, but this book is probably the closest. A majority of books on "biostatistics" shy away from mathematics and will focus only on preliminary concepts. Also, I have noticed that a lot of of them have gaps in the presented info and do not build up the topic in a logical Martin Bland is a recognized authority in the field. He has explained the concepts extremely clearly using true globe examples. This book does a very amazing job at covering nearly the entire spectrum of statistical way used in medical research with emphasis particularly on core things. In the appendices that follow (for example: in the chapter on regression) he has also discussed the mathematical basis for the presented material in a small bit more detail for the interested reader (continuing the same example: the least squares technique).I guess there is no universal optimal point for conceptual detail vs. mathematical rigor, and I would have personally liked to see more info about various distributions, their CDFs, moment functions, and so on. I believe that the book should assume at least high school level in mathematics i.e. logarithms, calculus, differential equations in one variable, and elementary true analysis. However, this remains a lacuna of the book, in my private opinion which will not be shared by others. Secondly, in the chapters on Bayesian methods and sample size, again I have felt that the author was torn between the need for comprehensive coverage vs. detail. Though I would have voted for a small bit more detail, I can't argue with problems of having a reasonable size and target audience of the book.Overall, perhaps one of the best books in the field, thought I could have done with some more mathematical rigor.

This is a amazing book! My professor used this for her class and I enjoyed it. I didn't obtain through the whole book but there is so much info within this text. It is useful because I can always report back to it when I need to. I am not planning on reselling this text because it will be useful to me.

A little book concerning Edward Levi's theory on legal reasoning. The size is perfectly compact, but don't allow that fool you. Levi's reasoning takes serious concentration to follow. By no means an "introduction" to the law, you should have a fairly amazing grasp on the workings of the court system before trying to finish this. The perfect fresh foreword to this edition by Schauer helps give required context. Recommended for anyone heading to law school or interested in legal theory.

Having some background in Hamiltonian Mechanics I decided to the book to learn something about aberrations in optics. Till chapter 4 I found the book interesting. It defines the optical lenght and explain Fermat Principle, define caracteristic funcions and deduce vectorial ray equations. Chapter 3 explains how necessary properties can be deduced from symmetry. Chapter 4 introduces various types of aberrations considering the displacement from the ideal imaged point. In paragraph 23. defines the effective aberration coefficients and from there on the book loose all his clarity. It changes several times the notation and writeslong expresion of 12 or more terms with so a lot of coeffiecients that is not posible to remember what are their meaning. I skiped paragraphs, pages and chapters but obtain the same stuff. So I have fun only 1/5 of the book (which is better than nothing...) and obtain disppointed from the rest.

Poor book. Maybe it's ok for those with a powerful math background, but for those of us that aren't majoring in pure mathematics, this book is far too dense and vague to fully comprehend. The book assumes that the reader knows a lot of theorems that aren't even presented anywhere between the covers. Most of the theorems that are presented are "left as an exercise" for the reader.

I considered this book for my course because it has the subjects I want: discussion of proofs, logic, functions and sets, and then applications to actual mathematics. the math subjects contain infinite cardinality, modular integers (I think), and true numbers including least upper ever it was my impression on reading a few sections that the discussion does not teach the material that well. Worse, for me at least, was what I consider a serious lapse of mathematical reasoning in the discussion of the very first example i looked at in the chapter on true ey defined upper bounds, and then gave as an obvious example of an unbounded subset of reals, the natural numbers. well that is not obvious at all, and it requires a non trivial proof to verify en they define the relevant concept, namely the "least upper bound" axiom, and assume it is happy byt he reals. Then they create a huge out of proving the archimedean property of the reals, which they do not bother to mention, is actually equivalent to the fact the natural numbers are are we supposed to react when the authors themselves do not seem to understand the subject they are pontificating about? It turns me off, especially at the exorbitant price.And although I am picking on this book, it is actually one of the best of them out there! A sad situation indeed, with regard to books on proofs and logic and applications.

This is a selected textbook for my course on Sustainability. The author gave a very amazing description on the environmental development in America. It is well written and simple to read. I have a much better knowledge on this topic after reading the book. The cost and quality of the book are amazing and it arrived timely. Satisfied with my purchase.

Firstly, I'll begin from positive side. This book is very helpful resource for a lot of numbers and events. Moreover, it is organized (divided into subtitles and sentences are bulleted), but I always lost track along with those a lot of bullets. Some chapters are not really bad. At least I thought that if I need some dates or names of organization, events, I learnt where I can search them easily (but Google is much easier, in fact). That's all my positive the negative points:Firstly hold in mind that that's introduction. It'll introduce you a lot of concepts which may familiar to you (mainly you feel that you are reading your old diary). Then it won't suggest any solution. From the reader's point of view, this book is totally written from the economist's view therefore overlooked some points regarding environment and failed to mention that environment is part of the sustainable development. Some info is a bit odd. I mean the mentioned standards in this book are not practiced in real-life. Moreover, most of examples biased towards favor of Globe Bank and other financial international organizations.Overall, this book poorly helped me to understand better about sustainable development due to its simplicity and bias, although I should mention that some (comparatively a few) ideas mentioned through the book were worth to read.

and had to rely on outside sources to obtain through the class. Seriously, my true analysis book is so much better (even though the class is so much harder). This book is a very dry read, and doesn't create reading through the chapters and examples worth it. The simple stuff? Yeah they've got you covered. But as you progress through the book, you'll search that the authors have left out quite a bit and don't explain anything intuitively at all, especially Chapter 3, which "covers" functions (I'm acing true analysis right now, but I still don't obtain what point of a function's image, as opposed to its range, is... Are they the same thing? The book doesn't respond that. Anyone who can, please reply). Chapters 4 and 5 are okay, and that's where my course stopped. I'm keeping the book as a resource for more advanced math classes, but most likely I'll just go search another book for that.

This is a amazing book. I highly recommend it if you are at all interested in genetic engineering. I have never studied molecular biology, and I've only taken high school chemistry, but the book really lays out the concepts well and I feel like I now have a amazing primary understanding of genetic engineering.

This is a amazing book for college students. Probably the best textbook of genetic engineering I've ever read ! I'm already a graduate student majored in plant science, but I still search this book quite useful in giving me an general and clear conception about genetic engineering. My favorite part is the concept maps at the end of each chapter !!

While this book does a decent job of covering all the material a student would need to create a smooth transition into abstract mathematics, I whole-heartedly agree with the reviewer below me when he described Bond and Keanne's coverage as being imperfect. However, when I say the coverage is imperfect I am referring to the methods in which the authors show the material rather than skipping over is critical to distinguish between what's covered and how the material is presented. So far as coverage is concerned, the authors obtain a 5 out of 5 in my book. Subjects covered include: Mathematical Reasoning, Sets, Functions, Binary Operations and Relations, The Integers, Infinite Sets, True and Complex Numbers, and latest but not least, Polynomials. This in my opinion is enough to prepare any student for higher level mathematics such as abstract alegbra, topology, number theory, and basically any other math course that emphasizes theory.When I first opened this book I knew I was going to have problems. All the examples in the book are jumbled together with propositions, corollaries, and theorems, which create them hard to stand out. Usually, books use various colors to point out examples from from the rest of the section, but for some reason this book does not do that. I really got the feeling that I was reading a story everytime I sat down to read through a section rather than reading a math condly, the examples themselves aren't even that great. While there is an abundance of examples in every section, most examples just state theorems or properties of functions. For example, on page 140 in chapter 4 on Binary Operations and Relations, Example 7 states "Let S be the set of all finite subsets of Z. Define R on S by ARB if |A| = |B|." That's it; no explination of what ARB means, no ere are two other gripes I have with the exmaples in this book. The largest of which is the fact that all throughout the book in every section of every chapter, the authors will just decide not to finish the examples and "leave it as an exercise" as if they were trying to create us suffer even more. In other words, they'll state a fact about something, and then decide that we should prove the claim they created on our so, the authors will oftentimes create references to former examples and propositions to contain in their examples which create it both confusing and irritating to have to look back at former examples just to be able to understand what they're talking about. Here's one final example to illustrate what I mean (no pun intended)Example 13 of chapter 4 on Binary Operations and Relations states as follows: "Let A be a set. The binary operation on P(A) defined in example 6 is both associative and commutative. This fact follows from parts 2 and 4 of Proposition 2.2.2 (a proposition stated in chapter 2)". What amazing does it do the student to know that if you don't have a photographic memory and are able to recall vividly what example/proposition they're referring to?All in all, this book had amazing intentions but a fresh edition is DESPERATELY needed. I would NOT recommend this book to a beginner of abstract mathematics unless this book is needed for class - and even then I'd be praying for you. If you wish a amazing introductory book, I would highly recommend "An Introduction to Mathematical Thinking" by Gilbert and Vanstone. That book does a really amazing job of presenting the method to approach theory and proofs and gives really good, thorough examples. In conclusion, the bottom line would be to stay far away from this book and obtain a various one. Satisfied hunting!

I just purchased this book and will modernize this review once the semester is over. I will be using this book with Mathematica for a graduate is was a amazing book for my composites class. I read 90 percent of this book for my class and it helped to understand the subjects of composite materials. This book was not very useful for the mathematics of composites and I had to reference several other books to obtain better understanding.

I've read four Data Science books this year, and this is my favorite so far. I particularly have fun that each chapter starts with a brief philosophical lesson, story and then ties them together thematically with the lesson (Saltz may have invented the Harold of technical writing).R is a bit of a mixed bag. If you're not a programmer, you'll probably love it. If you are, well my internal dialog went something like, "@*#(&*[email protected]!!!! Another 'language' to learn!" Luckily, R is more of an overgrown statistical pack than an actual is book is short, precise and to the point, and I wouldn't hesitate to recommend it.

Solid course book but a small too wordy at times. [email protected]#$%! was more technically written..personal preference. It seemed more geared toward the fine arts student than than the technical major.

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need pin to play rsweeps[] 2020-5-22 6:38Lost my pin for RSweeps

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An Introduction to Riemannian Geometry: With Applications to Mechanics and Relativity (Universitext)[] 2020-1-22 20:58I was completely happy with the book

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Special & General Relativity : A Beginner's Introduction to Basic & Advanced Concepts[] 2020-5-5 18:18👍

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