Sabtu, 19 Juli 2014

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File Size: 63203 KB

Print Length: 1104 pages

Simultaneous Device Usage: Up to 3 simultaneous devices, per publisher limits

Publisher: Wiley; 3 edition (July 12, 2017)

Publication Date: July 12, 2017

Sold by: Amazon Digital Services LLC

Language: English

ASIN: B073WND11W

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Amazon Best Sellers Rank:

#303,408 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

Don't listen to the other review! Lol, the solution is perfectly fine and if you purchased it by mistake, you can totally call Amazon right away and they will help you get your money back.​

This is to chemistry as that organic banana is to that regular banana.

Contains all of the answers to the “skill builder” sections of the 3rd edition textbook. It’s great if you need extra practice.

Easy to understand and thorough explanations

Everything you can expect

I bought this on accident: I meant to buy second edition, not third. And I can't return this. So I just spent $48 on nothing. Thanks, amazon.

I wasn’t able to use it. It was too different from the most recent edition.

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Minggu, 13 Juli 2014

Download Ebook , by Kim Scott

Download Ebook , by Kim Scott

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, by Kim Scott


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Product details

File Size: 7165 KB

Print Length: 269 pages

Publisher: St. Martin's Press; 1 edition (March 14, 2017)

Publication Date: March 14, 2017

Sold by: Macmillan

Language: English

ASIN: B01KTIEFEE

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Amazon Best Sellers Rank:

#5,852 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

Despite the 3 star review, I actually really liked this book. I had been looking forward to reading it for a while. The issue I had with the book can be illustrated by her performance|growth model. She spends a lot of time talking about the extremes but hardly any time talking about managing the middle, which is where probably 80% of managers really struggle with their direct reports!! I kept going back and scanning the pages again, thinking that I missed it. I could see a whole other book about that particular piece, and hopefully Scott will explore it further in a second edition. There were other similar gaps like that in the book - parts that I felt were explained so well at the extremes but things left unexplored, for example: companies whose culture is somewhere in the middle, managers who are dealing with performance in the middle, team dynamics somewhere in the middle. That "middle" is the tough part - how do you use Radical Candor to know when to pull the trigger on what when you're in a gray zone?

I hardly write reviews for books, but this one is worth the read. I'm only half way through and she's brought so much clarity to my management failures and triumphs. I now understand the things that made me fail my first time around and successful my subsequent times around. And now that I have a framework to understand, I feel like I can build a team that reflects accordingly.Good times. Thanks Kim. Is it too passive aggressive for me to give my current manager a copy of this book?

I've been at Google for 11+ years and much of what Kim talks about in the book resonated with me as a manager. This book as opposed to others I've read in the past has a ton of actionable guidance. I'm already looking for ways to apply many of the teachings from the book to my work. Especially the topics around Superstars and Rockstars hit home with me. Just today my team and I talked about how we could reward our Rockstars better. I also really like how Kim talks about the importance of being "centered" and how it's hard to be a good manager without being in a good place yourself.

A good read. Frankly some of the "bad" manager verbal assault on subordinates is a hard to believe, but that is what this book is written for. The basic thought on this book evolved around a. BUILD TRUST with your team. Them of you and you of them. It is the gateway to having foundational human relationships. Then b. BE CANDID with them (and them with you as the boss). Some good simple tips to focus on the activity, or the "it" - - NOT the person. The book was a little "round and round" on these two key points. Can really see how a newbie manager could benefit from this book.

As a Googler and startup founder, everything Kim talks about reasonates with me deeply. The approach to radical candor feedback, being truly transparent & balanced alongside caring for your team is the right modern approach to management. A great read for anyone considering starting a company or for managers everywhere.

As with many books in this genre, this one was helpful occasionally, too specific most of the time (expect to get nothing from the middle chapters if you aren’t in a tech firm), often self contradictory (“no one is a top performer” but a few pages later “reward your top performers”), and a quick read. I am glad I read it and I definitely took away some useful tidbits. Unfortunately, I think the key notions and examples could have been just as easily communicated in a blog post. I’m a little shocked the author has formed a whole company around this concept as it’s fairly simple. Tips about how to phrase feedback were especially useful, and many anecdotes were enjoyable. The text was, however, undermined by some baseless ageism (‘millennials do this or that’), needless repetition, and a little too much namedropping for my taste.

So I bought this book thinking I was buying “Fierce Conversations”. Turns out I was buying the wrong book - which turned out to be the best mistake I ever made because this book is way way better! This is hands down one of the best books I have read on leadership. The author takes a straight shooter, no nonsense, no BS, no pontificating approach to how to be a kick a$$ Manager! It’s great for leaders of all levels and walks through some foundational things (in a no nonsense way that doesn’t make you feel stupid) and then gets into how to actually establish trust with your direct reports. As in “say this” and “do this”. It is a very practical guidebook. I used an entire highlighter on every nugget I found - some pages are entirely highlighted!I will recommend this book to anyone I know. It is by far the most practical advice on getting things done, without leaving bodies in your wake.

When I read a comment like this is the "holy grail of management books", I have to scratch my head. This is a rehash of material covered in countless other management books. I would have expected better from someone with her resume!You can learn more from several of the Patrick Lecioni books and they are more fun to read. About halfway through the book, I stopped and donated to the library. This is suitable for a newer manager to read.

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Kamis, 03 Juli 2014

Ebook Free Numerical Linear Algebra

Ebook Free Numerical Linear Algebra

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Numerical Linear Algebra

Numerical Linear Algebra


Numerical Linear Algebra


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Numerical Linear Algebra

Review

' The authors are to be congratulated on producing a fresh and lively introduction to a fundamental area of numerical analysis.' G. W. Stewart, Mathematics of Computation'...Each lecture in the textbook is pleasantly written in a conversational style and concludes with a set of related exercises. This low-cost textbook emphasizes many important and relevant topics in numerical linear algebra and seems ideal for a graduate course as long as it is accompanied by a textbook with more mathematical details.' Ricardo D. Fierro, SIAM Review'Trefethen and Bau clear the dark clouds from numerical problems associated with factoring matrices, solving linear equations, and finding eigenvalues.' P. Cull, CHOICE'Just exactly what I might have expected - an absorbing look at the familiar topics through the eyes of a master expositor. I have been reading it and learning a lot.' Paul Saylor, University of Illinois, Urbana-Champaign'A beautifully written textbook offering a distinctive and original treatment. It will be of use to all who teach or study the subject.' Nicholas J. Higham, Professor of Applied Mathematics, University of Manchester"This is a beautifully written book which carefully brings to the reader the important issues connected with the computational issues in matrix computations. The authors show a broad knowledge of this vital area and make wonderful connections to a variety of problems of current interest. The book is like a delicate soufflé --- tasteful and very light." -Gene Golub, Stanford University."I have used Numerical Linear Algebra in my introductory graduate course and I have found it to be almost the perfect text to introduce mathematics graduate students to the subject. I like the choice of topics and the format: a sequence of lectures. Each chapter (or lecture) carefully builds upon the material presented in previous chapters, providing new concepts in a very clear manner. Exercises at the end of each chapter reinforce the concepts, and in some cases introduce new ones. ...The emphasis is on the mathematics behind the algorithms, in the understanding of why the algorithms work. ...The text is sprinkled with examples and explanations, which keep the student focused." -Daniel B. Szyld, Department of Mathematics, Temple University."...This is an ideal book for a graduate course in numerical linear algebra (either in mathematics or in computer science departments); it presents the topics in such a way that background material comes along with the course. ...I will use it again next time I teach this course!" -Suely Oliveira, Texas A&M University.

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Book Description

This is a concise, insightful introduction to the field of numerical linear algebra. The authors' clear, inviting style and evident love of the field, along with their eloquent presentation of the most fundamental ideas in numerical linear algebra, make it popular with teachers and students alike.

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Product details

Paperback: 184 pages

Publisher: SIAM: Society for Industrial and Applied Mathematics; 1 edition (June 1, 1997)

Language: English

ISBN-10: 0898713617

ISBN-13: 978-0898713619

Product Dimensions:

6 x 0.8 x 9 inches

Shipping Weight: 1.4 pounds (View shipping rates and policies)

Average Customer Review:

4.2 out of 5 stars

40 customer reviews

Amazon Best Sellers Rank:

#104,782 in Books (See Top 100 in Books)

This is without a doubt the most gentle treatment of not just algorithms and efficiency in numerical computations, but also the theory that allows these algorithms to work, and I really wish other books would follow suit. Too many books are more concerned with jamming ideas in your face over hundreds of topics because they fear becoming outdated in an ever expanding field (ESPECIALLY where linear algebra, or just vectors/data, is concerned).But this book has a clear purpose in mind. "This is a vector. A bunch of sorted data is a vector. This is how we need to handle it. This is how we're going to improve it. You can manipulate data like this, but not like that." And with that, you're left not just wanting more, but you're also fully prepared to tackle a more advanced text (like Iterative Methods for Sparse Linear Systems, an ideal "next step" from here. Or perhaps you're ready for linear programming/optimization methods? Or maybe even branching into nonlinear programming? Or convex analysis?). And you have the best foundation for being able to read through those jargon-heavy papers with giant summation signs and vector notation strewn everywhere without feeling "Oh, geez, another one of THESE papers."And this book, with all of its chapters and contents, is in no hurry to catch up with modern methods. It takes time to explain "Hey, look, we get that there are better ways of doing it. But the reasons those methods exist is because of what we're trying to show you."And the problems, wow! They're sorted into every possible category. You have your typical Simple - Challenging range, but you also have problems clearly designed for engineers with little abstract mathematical analysis ideas, problems clearly designed for computer scientists who have some knowledge but want something specifically applicable to them, problems clearly designed for the mathematician who can prove, and problems clearly designed for the mathematician who has more interest in application but needs more meat than the average engineer.And the presentation, wow! So much care is given to how much white space is needed between theorems, sections, equations, and algorithms. Trefethen and Bau know that math books, particularly numerical ones, tend to cram information too close together which can hurt the eyes.I'm absolutely gah-gah for this book. And you would be, too, if you sat down, read it, and worked through it. This is the second book I've ever had any desire to just sit down and try and work every problem through, and I'm almost done with it! And while there's only one book out there I frequently reread, this is one of the very books I keep coming back to when I need a quick reference while trying to sift through something like Bender's Decomposition or trying to construct a genetic algorithm.

This book is the best I have found for studying computational linear algebra. It is clearly written and well thought out. It might not be the best introduction to the subject, and something like Strang's Linear Algebra book is probably a better place to start out. The first few chapters are more of a review of an introductory linear algebra course, and assume that one has already seen standard topics like the definition of vector spaces, subspaces, spanning sets, linear independence, etc. However, for those who have taken a 1 quarter or semester course in linear algebra, this is the perfect place to go next.

Face it, most math textbooks are awful: boring to read, not much insight, little more than a compendium of definitions, theorems, proofs, and examples. Trefethen and Bau is an exception to that rule. Indeed, the field of numerical linear algebra is unusual in having available several top-notch textbooks: Golub and Van Loan, Stewart's two volumes, Saad's books on iterative methods, Demmel's introduction, Watkins' undergraduate level treatment, and T&B. All of these are excellent (and any student in numerical analysis should delve into all of them) but to my tastes T&B and Stewart are the standouts for insight and simply being fun to read.If you're a student using T&B in a course, to use it effectively you need to understand that T&B is a book to be read carefully for understanding; it's not a typical textbook suited only for "mining" for examples and solutions to homework problems. My students have sometimes complained -- accurately -- that T&B is short on details and worked examples, and many of the proofs are just sketches. But that's a feature, not a bug: you can learn much by filling in the missing steps. This is book for reading, so take the time to read it, to think about what you've read, and to fill in the gaps; it's worth it. If you need some worked examples, Watkins has them in great detail and would be a good supplement to T&B (though see the caveat below).The only minor gripe I have about T&B is that the order of topics (QR before LU before Cholesky) is unusual, which makes it a little awkward to coordinate with other books such as Watkins which do Cholesky before LU before QR.

I am a second year PhD student in Operations Research and for long I had been looking for a book in linear algebra to help me learn it myself (as I see that I need it no matter what research I want to do. It's just a good tool to know). One of my friends recommended this book to me, I got it and I am very happy with it. The book is great in different ways:-it is in the form of short lectures and for me who wants to learn linear algebra step by step, this is a perfect approach. You will have a 5-6 page lecture so whenever you start, you are set to finish that lecture.-It gives you intuition and understanding about what is really happenning geometrically which is amazing. To me, it is very important to have the "feeling" of what is happening because it is only then that you can think about bringing your real problem in this framework.-The examples in lectures clarify the subject while exercises give you a chance to learn even more.If you are new to linear algebra or know it but want to refresh your mind on intuitions and systematic thinking, I highly recommend this book.

Like this book a lot. I'm not a great mathematician so take this review with a grain of salt. But I had this book for a grad class and learned more computationally than I have in any other class.

Wonderful book, gives me a starting point for understanding most basic algorithms I come across as a user of linear algebra software.

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