Download The Oxford Frederick Douglass ReaderBy Frederick Douglass

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The Oxford Frederick Douglass ReaderBy Frederick Douglass

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The Oxford Frederick Douglass Reader collects in one volume the most outstanding and representative work from Frederick Douglass's fifty-year writing career, including all the major genres in which he worked: autobiography, journalism, oratory, and fiction. The Reader contains the following classic texts in their entirety: the landmark fugitive slave narrative Narrative of the Life of Frederick Douglass, An American Slave (1845); the consummate anti-slavery oration "What To the Slave Is the Fourth of July?" (1852); the pioneering novella The Heroic Slave (1853); and the magisterial analysis of lynching Lessons of the Hour (1894). Generous selections from Douglass's second autobiography, My Bondage and My Freedom (1855), illustrate his boldly revisionist personal and political agenda, while major chapters from both the 1881 and the 1892 editions of the final autobiography, Life and Times of Frederick Douglass, reveal the author's perspective on his own successes and his estimate of the nation's progress on the racial front in the post-war era. Also included are notable examples of Douglass's journalism, in which he advocated women's rights and black enlistment in the Civil War. In addition, the private as well as the public Douglass finds a voice in the Reader, as he responds to criticism of his decision to choose a white woman as his second wife and also discloses his carefully guarded views of religion through a little-known 1886 letter.
Editor William L. Andrews has provided an introduction and headnotes that give basic, accessible information regarding Douglass's life, writing purposes, and the reception of his texts, offering a thoughtful review of the crucial developments in Douglass's multiple careers as autobiographer, journalist, lecturer, and racial spokesman. The Oxford Frederick Douglass Reader provides students and readers with the most complete, diverse, and personally revealing record available of nineteenth-century black America's most celebrated writer.

• Sales Rank: #294708 in Books
• Published on: 1996-01-18
• Original language: English
• Number of items: 1
• Dimensions: 6.10" h x .94" w x 9.15" l, 1.20 pounds
• Binding: Paperback
• 384 pages

Review
"The most comprehensive collection on Douglass."--Iyunolu Osagie, Penn State

"A splendid, comprehensive anthology that contains the essential Douglass."--Robert E. Morsberger, California State Polytechnic University

"A comprehensive selection of Douglass' works...the volume provides an excellent overview of Douglass' career, and the chronology and introductory material also seem quite useful."--David M. Robinson, Oregon State University

"A most valuable and accessible volume--the best Douglass on the market for generalists. Excellent selection. Thanks for large type and generous spacing."--Agnes M. Jackson, The Claremont Colleges

"These are troubled times for black and white Americans, and Frederick Douglass's is a voice that needs to be heard. William Andrews' fine collection will ensure that Douglass again commands attention."--William S. McFeely, author of Frederick Douglass

"An excellent text."--Kay Rout, Michigan State University

From the Back Cover
The Oxford Frederick Douglass Reader collects in one volume the most outstanding and representative work of Frederick Douglass's fifty-year writing career, including all the major genres in which he worked: autobiography, journalism, oratory, and fiction. The Reader contains the following classic texts in their entirety: the landmark fugitive slave narrative Narrative of the Life of Frederick Douglass, An American Slave (1845); the consummate antislavery oration "What To The Slave Is The Fourth of July?" (1852); the pioneering novella The Heroic Slave (1853); and the magisterial analysis of lynching The Lessons of the Hour (1894). Generous selections from Douglass's second autobiography, My Bondage and My Freedom (1855), illustrate his boldly revisionist personal and political agenda, while major chapters from both the 1881 and the 1892 editions of the final autobiography, Life and Times of Frederick Douglass, reveal the author's perspective on his own successes and his estimate of the nation's progress on the racial front in the post-war era. Also included are notable examples of Douglass's journalism, in which he advocated women's rights and black enlistment in the Civil War. In addition, the private as well as the public Douglass finds a voice in the Reader, as he responds to criticism of his decision to choose a white woman as his second wife and also discloses his carefully guarded views of religion through a little-known 1886 letter. Editor William L. Andrews has provided an introduction and headnotes that give basic, accessible information regarding Douglass's life, writing purposes, and the reception of his texts, offering a thoughtful review of the crucial developments inDouglass's multiple careers as autobiographer, journalist, lecturer, and racial spokesman. The Oxford Frederick Douglass Reader provides students and readers with the most complete, diverse, and personally revealing record available of nineteenth-century black America's most celebrated writer.

About the Author
William L. Andrews is at University of Kansas.

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Ebook Serving the PackBy Ellie Saxx

Ebook Serving the PackBy Ellie Saxx

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Serving the PackBy Ellie Saxx

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Warning: This story contains the explicit details you've come to expect from Ellie Saxx. Content includes graphic descriptions of sex acts, including masturbation, oral sex, anal sex, double penetration, group sex, gangbang sex, and at times the action gets a little rough. Open-minded adults only!

• Sales Rank: #184797 in Audible
• Published on: 2013-08-14
• Format: Unabridged
• Original language: English
• Running time: 45 minutes

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Download Evelyn Wood READING DYNAMICS A Video/DVD Workbook (The World Famous Speed-Reading Program)By Evelyn Wood

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Evelyn Wood Reading Dynamics. The world Famous speed reading program. DvD and a video/dvd workbook.

• Sales Rank: #604876 in Books
• Brand: Generic
• Published on: 1993
• Format: DVD
• Binding: DVD-ROM

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PDF Ebook Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

PDF Ebook Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

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Review

This comprehensive book should be of great interest to learners and practitioners in the field of machine learning.―British Computer Society

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Review

An astonishing machine learning book: intuitive, full of examples, fun to read but still comprehensive, strong and deep! A great starting point for any university student―and a must have for anybody in the field.―Jan Peters, Darmstadt University of Technology; Max-Planck Institute for Intelligent SystemsKevin Murphy excels at unraveling the complexities of machine learning methods while motivating the reader with a stream of illustrated examples and real world case studies. The accompanying software package includes source code for many of the figures, making it both easy and very tempting to dive in and explore these methods for yourself. A must-buy for anyone interested in machine learning or curious about how to extract useful knowledge from big data.―John Winn, Microsoft Research, CambridgeThis is a wonderful book that starts with basic topics in statistical modeling, culminating in the most advanced topics. It provides both the theoretical foundations of probabilistic machine learning as well as practical tools, in the form of Matlab code.The book should be on the shelf of any student interested in the topic, and any practitioner working in the field.―Yoram Singer, Google Inc.This book will be an essential reference for practitioners of modern machine learning. It covers the basic concepts needed to understand the field as whole, and the powerful modern methods that build on those concepts. In Machine Learning, the language of probability and statistics reveals important connections between seemingly disparate algorithms and strategies.Thus, its readers will become articulate in a holistic view of the state-of-the-art and poised to build the next generation of machine learning algorithms.―David Blei, Princeton University

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Product details

Series: Adaptive Computation and Machine Learning series

Hardcover: 1104 pages

Publisher: The MIT Press; 1 edition (August 24, 2012)

Language: English

ISBN-10: 0262018020

ISBN-13: 978-0262018029

Product Dimensions:

8 x 1.6 x 9 inches

Shipping Weight: 4.3 pounds (View shipping rates and policies)

Average Customer Review:

4.1 out of 5 stars

96 customer reviews

Amazon Best Sellers Rank:

#22,772 in Books (See Top 100 in Books)

In a nutshell, the value of reading Murphy's Machine Learning highly depends on what you expect to get out of it.------------------As a graduate student who had read a descent number of papers in the field, I feel very conflicted about this textbook.------------------If you expect to teach yourself machine learning from this textbook, this is in my opinion almost surely *not* the textbook to get. (0/5 Stars)-The content of the textbook is highly disorganized. Future chapters are constantly referenced in the text (as if you have already read them!). Perplexingly, meaningful explanations of concepts are often delayed by multiple chapters. (Ex. BIC is introduced in Ch.6 but a mathematical justification is provided only in Ch. 8 when the mathematical justification could have (and should have) been in Ch. 6).-A number of topics are merely mentioned (like VC dimension) but not actually discussed at any reasonable length, making some sections of the textbook meaningless.-I would instead recommend the related (but different) text Introduction to Statistical Learning with Applications in R as it is quite accessible.-----------However, if you are an instructor and wish to use this textbook as a supplement to a course or are a researcher then Murphy's Machine Learning is in my opinion could be a worthwhile purchase. (4/5 stars)-The examples, references and illustrations give the textbook a particularly nice touch. (I particularly enjoyed the example of calculating the posterior probability of user ratings of two different items on Amazon).In summary, if you are an instructor that wants their students to learn how to read challenging exposition to prepare them for reading research papers in the field or if you wish to use this as a reference, then this is a good choice. Otherwise, pass.

(Disclaimer: I have worked with a draft of the book and been allowed to use the instructor's review copy for this review. I have bought the book from Amazon.co.uk, but apparently this Amazon.com review can't be tagged "verified purchase". I don't receive any compensation whatsoever for writing this review. I hope it will help you chose a machine learning textbook.)Similar textbooks on statistical/probabilistic machine learning (links to book websites, not Amazon pages):- Barber's Bayesian Reasoning and Machine Learning ("BRML", Cambridge University Press 2012)- Koller and Friedman's Probabilistic Graphical Models ("PGM", MIT Press 2009)- Bishop's Pattern Recognition and Machine Learning ("PRML", Springer 2006)- MacKay's Information Theory, Inference and Learning Algorithms ("ITILA", CUP 2003)- Hastie, Tibshirani and Friedman's Elements of Statistical Learning ("ESL", Springer 2009)* Perspective: My perspective is that of a machine learning researcher and student, who has used these books for reference and study, but not as classroom textbooks.* Audience/prerequisites: they are comparable among all the textbooks mentioned. BRML has lower expected commitment and specialization, PGM requires more scrupulous reading. The books differ in their topics and disciplinary approach, some more statistical (ESL), some more Bayesian (PRML, ITILA), some focused on graphical models (PGM, BRML). K Murphy compares MLAPP to others here. For detailed coverage comparison, read the table of contents on the book websites.* Main strength: MLAPP stands out for covering more advanced and current research topics: there is a full chapter on Latent Dirichlet Allocation, learning to rank, L1 regularization, deep networks; in the basics, the decision theory part is quite thorough (e.g. will mention Jeffrey's/uninformative priors). The book is "open" and vivid, doesn't shy away from current research and advanced concepts. This seems to be purposeful, as it shows in many aspects:- quotes liberally from web sources, something usually not done in academic publications- borrows "the best" from other authors (always with permission and acknowledgment, of course): most importantly the best pictures and diagrams, but also tables, recaps, insightful diagrams. Whereas other books will produce their own pictures and diagrams themselves (eg, PRML has a distinctive clarity and style in its illustrations), MLAPP takes many of its colour illustrations from other people's publications; therefore it can select the most pithy and relevant pictures to make a point. You could think that reproductions may be illegible and require extra effort to interpret because they come from a variety of sources; I have found that the bonus coming from having precisely the right image prevails.- frequent references to the literature, mentions of extensions and open questions, as well as computational complexity considerations: for instance, the section on HMMs will mention duration modeling and variable-duration Markov models, and a comparison of the expressive power of hierarchical HMMs versus stochastic context-free grammars, complete with relevant citations, and a brief mention of the computational complexity results from the publications. All this connects the material with research and new ideas in a fine way -- which other textbooks don't achieve, I find. For instance, PGM defers references to a literature section at the end of each chapter, resulting in a more self-contained, but more poorly "linked" text.* Didactic aids: Another distinctive feature is that the author clearly has tried to include didactic aids gathered over the years, such as recaps, comparative tables, diagrams, much in the spirit of the "generative model of generative models" (Roweis and Ghahramani): e.g. table comparing all models discussed, pros and cons of generative vs. discriminative models, recap of operations on HMMs (smoothing, filtering etc), list of parameter estimation methods for CRFs.* Editorial features: Other editorial features worth mentioning are- compared to others, helpful mentions of terminology, e.g. jargon, nomenclature, concept names, in bold throughout the text ("you could also devise a variant thus; this is called so-and-so")- mathematical notation relatively clear and consistent, occasional obscurities. PGM stands out as excruciatingly precise on this aspect.- boxes/layout: no "skill boxes" or "case study boxes" (PGM), not many roadmap/difficulty indications like ITILA or PGM, examples are present but woven into the text (not separated like PGM or BRML). Layout rather plain and homogeneous, much like PRML.- sadly lacks list of figures and tables, but has index of code* Complete accompanying material:- interesting exercises (yet fewer than PRML, BRML, PGM); solutions, however, are only accessible to instructors (same with BRML, PGM), which in my experience makes them only half as useful for the self-learner. PRML and ITILA have some solutions online resp. in the book.- accompanying Matlab/Octave source code, which I found more readily usable than BRML's. PGM and PRML have no accompanying source code, even though the toolkit distributed with Koller's online PGM class might qualify as one. I find accompanying code a truly useful tool for learning; there's nothing like trying to implement an algorithm, checking your implementation against a reference, having boilerplate/utility code for the parts of the algorithm you're not interested in re-implementing. Also, code may clarify an algorithm, even when presented in pseudo-code. By the way, MLAPP has rather few pseudo-code boxes (like BRML or PRML, while PGM is very good here).- MLAPP is not freely available as a PDF (unlike BRML, closest topic-wise, ESL, or ITILA). This will no doubt reduce its diffusion. My own take on the underlying controversy is in favor of distributing the PDF: makes successful books widely popular and cited (think ITILA or Rasmussen and Williams' Gaussian Processes), increases the book's overall value, equips readers with a weightless copy to annotate with e-ink, or consult on the go. I believe PDF versions positively impact sales, too: impact neutral-to-positive to course textbook/university library sales, indifferent to sales in countries with widely different purchase power, positive to all other segments due to enormous diffusion/popularity.* Conclusion:The closest contender to this book I believe is BRML. Both are excellent textbooks and have accompanying source code.BRML is more accessible, has a free PDF version, and a stronger focus on graphical models.MLAPP has all the qualities of an excellent graduate textbook (unified presentation, valuable learning aids), and yet is unafraid of discussing detail points (e.g. omnipresent results on complexity), as well as advanced and research topics (LDA, L1 regularization).

I'm sure if you are a Google Research Scientist and are not learning the material for the first time, this book is amazing. For everyone else, I would not recommend it. I bought this book for my Fall 2013 COMPSCI 571 class, and I regret it. Before buying this book, consider the following:1. Take a look at the online Errata. This book is already in it's 3rd printing and it just came out. The list of corrections for this (the 3rd edition) is already mind-numbingly long. The 4th printing coming out this month will surely fix some errors, but there are just too many.2. Our class has an online forum (for a 100 person class) where we discuss topics, and most questions are either (a) basic topics from the book that no one understood or (b) talking about how one figure in the book has multiple errors associated with it. At first I was really excited to find mistakes and submit them to the Errata - it was like I was part of the book! Now I just get frustrated and have already given up on submitting corrections.3. Our instructor regrets using this book and modifies the examples before giving them to us in class. Our out of class readings now consist mostly of MetaAcademy.com.4. There are hardly any worked-through examples, and many of those that are worked through have errors.5. Many important concepts are skimmed over way too quickly. For example, there is a whole chapter on Logistic regression. However, Logistic regression is covered for exactly 2 pages. Then a weird 3D graph is presented but not explained (a common theme throughout the book is graphs that look absolutely amazing, but which convey little information as to exactly what's going on to a lay-person like me), then the rest of the chapter presents methods for doing the math, which I'm sure are useful in some sense, but I'm still thinking: "why is this MLE not in closed form, what is a Hessian doing here... and wtf is going on?!"Most students just got the PDF for free online, and I would highly suggest doing something other than paying $55 for this book.

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Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) PDF

Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) PDF

Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) PDF

Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) PDF

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Ebook Download As You Are: Ignite Your Charisma, Reclaim Your Confidence, Unleash Your MasculinityBy Nick Sparks

Ebook Download As You Are: Ignite Your Charisma, Reclaim Your Confidence, Unleash Your MasculinityBy Nick Sparks

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As You Are: Ignite Your Charisma, Reclaim Your Confidence, Unleash Your MasculinityBy Nick Sparks

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You've been in that zone where socializing, both platonic and romantic, comes easy -- but most of the time you're not there. Around the women who intimidate you most you struggle to think of what to say, sabotage yourself in ways you don't fully understand, and feel confused about when and how to express your sexuality. You worry that you'll have to settle for someone who you're not all that excited to be with (if you're lucky enough to find anyone) and/or face a messy divorce when it inevitably doesn't work out.

That's why I wrote this book.

I've coached men on improving their social and dating lives for over a decade, charging thousands of dollars for a weekend program, appearing on national news outlets, and amassing millions of views on youtube. I have a success rate with my clients that puts the rest of the industry to shame, and this book represents the very best of what I teach.

I want to make this knowledge available now because I know what it's like to feel as though you'll have to settle for whatever comes along... like the women you really want to be with are speaking a different language. I wrote this book because I wish I had it back in middle school.

This isn't a collection of pickup lines or tricks. Let's face it - if those worked, you wouldn't be reading this right now.

Simply put, this book teaches you to be that person you are when you're "in the zone" all the time. It's about stripping away all the things that are keeping you from being naturally attractive. You've always known that, "just be yourself," was good advice, otherwise it wouldn't be repeated so often. This is the book that finally explains how to do it.

In this book you're going to learn:

- How to eliminate "rejection"

- Why the words you say don't really matter

- The action to take that will always get you "in the zone"

- How to identify the women that really want you to approach them

- Understanding what flirting means, and how to become a master at it

- What to text if she doesn't respond

- How to know exactly when she wants you to make the move

- What to say to start a conversation in any situation

- How to make conversations with people who intimidate you flow as smoothly as chats with your best friends

- How to get her to contribute equally to the conversation so you don't do most of the talking and run out of things to say

- How to easily overcome awkward silences

- The secret to being funny

- How to move an interaction forward sexually without ever worrying about being called "inappropriate" or "creepy"

- How to get a phone number that turns into a date 90% of the time

- How to ensure your dates are charged with sexual tension rather than ending in an awkward kiss attempt

- The way sexual attraction actually works, and why the lessons you've learned your entire life are wrong

- How to turn a friendship into something more

- How to build a social circle so you'll always have a "wingman" or someone to hang out with

- How to always look great, even if you're shopping on a budget

- How to scream confidence with your body language instead of insecurity

- The difference between "He was ok" and "He's awesome"

- How to develop yourself into the man who naturally attracts the woman (or women) you really want

Don't expect anything overly-complicated. You'll find yourself saying, "it can't be this easy," more than once - only to discover that you're the one who's been making it difficult the entire time.

Enjoy!

Disclaimer: The language I use throughout this book represents men communicating with women because that's what I've successfully taught hundreds of guys to do. My advice, however, applies to anyone, man or woman, who's looking to improve their platonic and romantic communication with anyone else.

• Sales Rank: #27524 in eBooks
• Published on: 2015-10-05
• Released on: 2015-10-05
• Format: Kindle eBook

About the Author
Nick Sparks is a professional dating coach who, at 32 years of age, has successfully helped thousands of men live the social and dating lives of their dreams, been featured on CNN and various other international news outlets, amassed millions of youtube views, and, most recently, has become a #1 Amazon bestselling author. When he’s not pondering the deepest questions of human connection, Nick can be found enjoying nature, cheering on his Michigan Wolverines, and enjoying new experiences in the company of his dearest friends.

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Ebook Leading Lean Software Development: Results are Not the Point (Addison-Wesley Signature)

Ebook Leading Lean Software Development: Results are Not the Point (Addison-Wesley Signature)

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Leading Lean Software Development: Results are Not the Point (Addison-Wesley Signature)

Ebook Leading Lean Software Development: Results are Not the Point (Addison-Wesley Signature)

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Currently this publication is presented for you the book lovers. Or are you not kind of publication enthusiast? Never mind, you could likewise read this book as others. This is not type of required book to refer for sure community. However, this book is likewise referred for everybody. As recognized, every person could get the developments and expertise from all book types. It will certainly depend on the personal preference and has to check out certain book. As well as once again, Leading Lean Software Development: Results Are Not The Point (Addison-Wesley Signature) will certainly be readily available for you to get that you need and want.

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Exactly what regarding Leading Lean Software Development: Results Are Not The Point (Addison-Wesley Signature) If that relates to your problem, it will certainly not only provide those concepts. It will give instances, very easy and simple examples of just what you should carry out in settling your troubles. It will likewise show up the outcome and also sort of the book that reads. Many individuals are falling in love in this book because its power in order to help everyone improve.

• Published on: 1600
• Binding: Paperback

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