Machine Learning Books

Gregor McLennan's "Marxism and the Methodologies of History" is out of print, which is truly unfortunate, since it's an excellent (if perhaps obscure) book. In this book McLennan, a historian by trade, undertakes an exceedingly informative and thorough survey of historiography and historical methodology, from all possible political quarters and stylistic approaches. Explaining, criticizing and evaluating each, McLennan tries to work towards a useful and usable historical materialism that can learn from prior approaches and yet transcend them, which he finds in the approach dubbed "critical realism".

Although much of the book is devoted to in-depth discussion of historians and historiographers of the past and their relative merits, McLennan is a good writer, making sure that despite its high academic level the book does not become boring. For anyone not thoroughly versed in methodological and philosophical issues in the field of history, "Marxism and the Methodologies of History" will be very informative and enlightening, and the author's judgements are refreshingly objective, nuanced and even-handed for a book with "Marxism" in the title. McLennan nevertheless does not shy away from controversial conclusions, as in the first part of the book where he ends up concluding that Marxism cannot exist on its own as an identifiable 'philosophy of history'.

Many of the main aproaches within Marxism (I say 'approach' as to not prejudge whether they ought to be called philosophies or not) are discussed in particular depth, including but not limited to Althusser, Braudel and the Annales School, and Alfred Soboul. There are additionally chapters on the use of the theory of 'labor aristocracy' in historical method, on Marx & Engels' own historical approaches, and on the use of so-called 'social history'. But many more familiar and famous names in history appear, from E.P. Thompson to Johan Huizinga. It is definitely an advantage in reading this book to be familiar with at least the more important ones of these, as well as with at least basic philosophy of history (such as the important distinction between descriptive sequences and causal sequences). Nonetheless, the intelligent reader even uninformed about any of this can figure it out as he goes along, thanks to McLennan's densely informative style.

For anyone interested in Marxism and/or history and historiography, this book is much recommended reading.

The aim of the book is to bring together key papers in Machine Learning and to provide an introduction to the field and a reference collection for graduate students and researchers. The book contains 51 most imoportant article from Machine Learning (up to 1990). Most of these are NOT available online, so watch out! The following areas are covered: Introduction (3 papers; one by Simon), Inductive Learning From Preclassified Training Examples (16 papers including great classics from Quinlan, Michalski, Mitchell, Minsky...), Unsupervided Learning and Concept Discovery (9 papers -- Feigenbaum, Holland...), Improving the Efiiciency of a Problem Solver (10 papers including fameous Samuel's gem "Some Studies in Machine Learning Using the Game of Checkers"; also papers from Mitchell, Nillson, Utgoff...), Using Preexisting Domain Knowledge Inductively (13 papers; Russel, etc...). Really really outstanding collection and a definite recommendation.

But why not write one more page? It just left me wanting more. And the surprise ending was my favorite part -- but I won't ruin it for other readers (hint -- it involves a watermelon.)

I ordered this book to help prepare our entry in next year's competition. It looks like we are not going to make it, but I am still glad I ordered RoboCup. Almost 800 pages of robot know-how plus tons of illustrations - it just keeps on giving! This has been and will continue to be a great source of information for my other robotics projects. The RoboCup books are one of the best-kept secrets to success in amateur robotics.

A programmable digital computer, based on Alan Turing's design, ran its first program in 1950 at the National Physical Laboratory, London. Even today, every computer in the world remains computationally equivalent to a Turing Machine. It is little known however, that Turing also investigated neural network architectures as early as 1948, and before the term genetic algorithm was coined, proposed configuring his networks with a "genetical search". In this book Teuscher presents the most extensive exploration of Turing's neural networks available. The book contains over 100 diagrams, detailed examinations of the logical behaviour of Turing's networks, experiments into their emergent properties and extensions of Turing's ideas based on recent findings. An understanding of Turing's networks allows insight into a number of modern research areas such as Kauffman's work on the principles of self-organisation, the boundaries of computability, and even the real neural networks of living things (Turing claimed that his neural networks were probably the simplest possible model of the human cortex). Because the discussion in the book starts with Turing's early networks and progresses through to current research, it can also be read as an accessible overview of the history of the field. In addition, the book makes it clear that there are many interesting research questions still to be answered in this area. As such, this book will be of interest to historians of computer science and modern researchers alike.

My toddler loves this book so much, the library should just sell it to us! That's why I'm buying it now. It's from British publisher Usborne, so some words may seem different to an American audience. However it doesn't impede the great artwork or the myriad farm equipment explained in the pages. Usborne typically produces quality books, and this one is no exception.

Verbmobil: Foundations of Speech-to-Speech Translation

This exceptionally readable (in English) account of the German Verbmobil project (1992-2000) is comprised of 47 contributions from the principal participants in the project. These contributions cover all aspects of this major effort in natural language processing under the headings:

- Introduction (Overview by editor) - From Speech Input to Augmented Word Lattices - Lexical and Syntactic Processing - Semantic Processing - Dialogue Translation - Dialogue Processing and Context Evaluation - Language Generation and Speech Synthesis - Data Collection and Evaluation - System Architecture and Software Integration.

The project culminated in a working prototype which allows bi-directional telephone dialogues in three discourse domains: Appointment Scheduling, Travel Planning and Remote PC Maintenance,- between German, Japanese and American-English speakers.

The work reported,

- represents the state of the art in Speaker-Independent Spontaneous Dialogue Recognition, Translation and Speech Synthesis, - provides quantitative data which illustrate the strength and weaknesses of symbolic and statistical approaches to translation in this context. - illuminates the tradeoffs in various approaches to deep linguistic analysis - illustrates the important role of acoustical and lexical data collection and processing. - gives insight into the interaction between the many modules as reflected in the detailed End-to-End evaluation of the system and its components - demonstrates the role of the underlying system and software architecture in providing both, a test-bed development environment and the basis for a near-real-time demonstration system. - reflects upon some of the management issues encountered in a project of this scope

The reported work includes a number of advances, including

- a speech controlled telephone dialogue system including speaker-language identification - integration of deep and shallow processing: results from concurrent translation threads. - systematic use of (multilingual) prosodic information at all processing stages, - Parsing, Dialog Understanding, Translation, Generation and Speech Synthesis - understanding of spontaneous speech repair - generation of dialogue summaries

The people responsible for editing this volume have raised the bar for technical writing. The result is an unusually lucid, concise and consistent exposition of work from several disciplines, generally only accessible to the specialists. Limiting the length of the individual contributions, has confined the reporting to what was accomplished in the course of the project., without compromising scientific rigor. If I have any criticism at all, it is the lack of a subject and author index and the occasional use of abbreviations not spelled out, at first use, within an article.

To those interested in speech recognition and machine translation, this is essential reading; - they'll be surprised to find it satisfying as well.

Those concerned with large-scale, distributed software development will find several new benchmarks in this project.

See also for a project overview. .

This book makes a great text for graduate courses, as well as a reference for scholars. The chapters are well written and provide good examples for any significant concepts. Each section covers the basics to establish a foundation of understanding for someone unfamiliar with the area, but goes on to also touch upon the research forefront on each topic. One of the most useful sections I've found as a researcher is the Bibliographic Notes found at the end of each section which briefly describes the major groups of work within the topic with cites to major papers/articles/books in each of these areas (seems to be about 50 or so per chapter).

The only "drawback" to this book would be if you wanted to touch upon everything, there is far too much content for a single semester. However as mentioned above, the chapters are structured such that you could easily use the first couple sections of each chapter to cover all the foundations and either leave later sections for students to read on their own/select an advanced project, or cover the remainder in a 2nd semester.

I highly recommend this book to any graduate looking for a comprehensive text and reference on web mining.

(In the interest of full disclosure, I am listed in the acknowledgements from providing feedback on a pre-print edition of the text that was used as our course textbook. I do not get royalties from sales in any way.)

Another book that Dr. L had us read. During the 2008 presidential debate I see one party is trying to buy votes even though the failures of socialism have been proven time and time again throughout history. This is the singular short work on the failures of socialism.

Friedrich Hayek's The Road to Serfdom was written at a time when the Labour Party of Britain was openly socialist. Although modern social democrats renounce the 's' word, socialism is indeed the root of their thinking, and in this exposition, his magnus opus, Hayek unabashedly sends socialism to the gutter where it belongs. Hayek's thesis, that socialism and totalitarianism are two birds of the same feather, has stood the test of time, and it continues to show up today in the cases of Venezuela or Bolivia. Hayek was arguably responsible for Labour's (and the Democrats') turn to the right, set in stone by former PM Tony Blair (and former President Clinton). This book is, however, still very relevant, exemplified by the Democrats' plan to invade the health care sector, the countless bureaucracies located in Washington, and President Bush's reckless invasion of privacy (which is related to Hayek's arguments about war time and peace time). Although Hayek often comes off as soft on a number of issues, he could not be nearly as dedicated as Milton Friedman to absolute freedom because the intelligentsia was on the far-left in the 40's.

For classical liberals, modern leftists, and conservatives alike, The Road to Serfdom is extraordinarily eye-opening.

The only, effective way to reject socialism is by attacking it's fundamental philosophical ideas. That collectivism is good and the individual must be sacrificed for the "good of the people". Attacking a philosophy such as communism or socialism, because it is not "practical" is a contradiction and undercuts any argument against such a corrupt philosophy. These ideas are not good in theory but bad in practice. They are evil in theory and therefore evil in practice.

I would like to also recommend Ayn Rand's, "The Virtue of Selfishness". This is THE work to understand Man's Individual Rights based on His Rational Nature. It is from these fundamental Truths that the ONLY proper function of a legitimate government is derived - The protection of Individual Rights.

Considering it my duty as an economics major, I took it upon myself to read this book, with little expectations as to its brilliance, and was completely swept away. Not only is Hayek extremely eloquent in articulating the case for free trade, he supports his arguments with facts (e.g. what was then going on in Nazi Germany) and with theory (e.g. why without even the historical evidence that we do have we must conclude that a centralized system cannot equally favor everyone).

Since it is my tendency to look at the 1 star reviews before making a 5 star one, I recognize that some people don't like Hayek because he doesn't recognize the great things about socialized medicine (like how a guy in Canada signed up for a CAT scan under his dog's name because animals are not covered under their highly efficient centralized health care...true story by the way) or the kind thoughts of socialist thinkers (please don't make me choose my selection of Marx quotes). But what Hayek does is present a prima facie case against socialism; before anyone can advocate socialism, they MUST address Hayek's arguments.

This is why I think before any socialist and libertarian face each other in a squabble, both must have read The Road to Serfdom so that they can hit on the applicable issues instead of babbling on about poverty statistics. Are you a socialist and disagree with Hayek? Fine, but read the book so that you know where your opponents stand. I really think that socialists think lovers of capitalism are greedy and have no ethics. But if you read our spokesman Hayek, you'll see why we think that the free market is actually BETTER for society.

Let's change the scope of the argument. Socialists should stop arguing about how some people are poor...yes, some people are poor...and demonstrate how a centralized system can make people BETTER than they would be under the free market system. How planning the systems of production would be more efficient and prosperous than under the system of competition. How giving all our freedoms to one entity would guarantee them for all. If you can effectively address these issues and the many more that Hayek brings up, we will soon see a blessed change in the current headache of debates on socialism.

Friedrich August von Hayek was an Austrian-British economist and political philosopher known for his defense of classical liberalism and free-market capitalism against socialist and collectivist thought in the mid-20th century. Since 1920s, he worked in Austria. Unwilling to return to Austria after its annexation to Nazi Germany, Hayek became a British citizen in 1938, a status he held for the remainder of his life. It was during this time that "The Road to Serfdom" originated, originally published by Routledge Press in March 1944 in the UK and then by the University of Chicago in September 1944.

Hayek's central thesis of this book is that all forms of collectivism lead logically and inevitably to tyranny, and he used the Soviet Union and Nazi Germany as examples of countries which had gone down "the road to serfdom" and reached tyranny.

The book has many worthy observations. For example, all people are different by their mental development (which is also influenced by family environment and education, not counting the physical differences of the brain and endocrine system) and thus the classes of the society are needed at least to give more developed people to fully put into action their potential. Liquidation of social classes will also liquidate the abilities of more developed individuals. The same is on the international level. Consider international planning. Whichever honest and democratically open panning system will be adopted, it will be opposed by less developed and poorer nations, because they will see it as ignorance or oppression of their interests. This is obvious - the needs and goals of poor or underdeveloped countries cannot match the goals of rich or developed countries; as the interests of more educated people cannot match the interests of less educated ones.

Many people came to a conclusion that the wealth, in some extent, depends on a level of education. The problem is that not all the people in equal extend incline to the education, to their self-improvement. This is because of the differences of their needs, habits, abilities, capabilities, and so on. Leo Tolstoy in his novel "Resurrection" arose a question of how to improve the level of education: from inside of each individual or from outside? Which came first, the chicken or the egg? Should first the level of education in the society be risen which yields a revolution (dialectic transition of quantity into quality) or the revolution should make the environment to foster the education. Hayek doesn't explicitly raise this issue, but brings parallel between delegation of decision making in managing an enterprise and managing the state. Hayek thought that if a company boss makes all decision making solely by himself and doesn't give the work (of decision making) back to the people (see Ronald Heifetz's publications), it is similar to the states with totalitarian government. Such a dictatorship, enterprise-wide or country-wide, can be used in particular circumstances, but should not be used in all cases as the absolutely correct way of management, according to Hayek.

I would recommend this book to anyone looking to learn the basics of computation theory and formal languages or for someone looking to revisit this material after an absence.

The book is very readable and covers the basics in a systematic fashion. I haven't looked at this material since my university days, but found it very easy to read and digest.

I had read a few other books on automata, but I was not able to get clear notion about pumping lemmas, decidability and so on. However, when I read the 1st edition of this book, finally, I got those concepts. One of great things in this book is proof ideas. This book has very clear and concise explanations about proofs.
I bought 2nd edition of this book, since it has lots of solved problems and exercises. those solved problems will boost your understanding the text and they contains a few things you should know, but omitted in the text.
If you don't understand many concepts in automata and computability with other textbooks, I strongly recommend this book.

This is a great book. The topics are covered in a clear and interesting way. I came to this book after having been exposed to NFA's and DFA's in a compiler course and this exposition is much more enlightening. The proofs in this book are very well written in my opinion, very clear. Studying proof techniques in a book such as Solow's "How to Read and Do Proofs" will prepare you well to understand the proofs in this book.

I recently encountered this book at a publisher's booth at a computer conference and read it on the ride back home. This morning I made a trip to the college bookstore and notified them that it is the textbook that I will be using in my computation theory class this spring.
The chapter titles are:

0) Introduction - this chapter contains the fundamental mathematical background of sets, functions, graphs and proofs. For most students, it could be skipped or skimmed.
1) Regular languages - this chapter is an introduction to deterministic and nondeterministic finite automata and regular expressions.
2) Context-free languages - an introduction to context-free grammars and pushdown automata.
3) The Church-Turing theses - an introduction to Turing machines and the variants, such as multiple tapes and nondeterministic Turing machines.
4) Decidability - the definition of decidability and how Turing machines and finite automata are used to prove or disprove if a language is decidable.
5) Reducibility - the definition of reducible and how Turing machines can be used to execute reductions.
6) The recursion theorem - an introduction to the recursion theorem and some applications to formal theories.
7) Time complexity - the first chapter in the coverage of algorithmic complexity, in this case execution time.
8) Space complexity - an examination of the complexity of algorithms from the perspective of the amount of memory required.
9) Intractability - an examination of the problems that can be solved in principle but not in practice.
10) Advanced topics in complexity theory - approximation algorithms, probabilistic algorithms, alternation, interactive proof systems, parallel computation and cryptography.

There is less coverage of grammars than most books, which is replaced by more in the area of algorithmic analysis. In my opinion, that is an appropriate tradeoff, the analysis of algorithms gives the students some understanding of how automata are applied in computer science.
Another excellent feature of this book is the solutions to selected exercises that appear at the end of the chapters. My estimate is that reasonably detailed solutions to approximately one-third of the problems are included. This allows the students to work extra problems by themselves, and helps the instructor if they are asked to do another example in class that they have not already worked through.
The exposition is very good; I am convinced that the students will be able to read the material on their own, which is one more reason why I adopted this book for my course.

Go buy an international version which is a lot cheaper than this, and they have the same contents. This version is also printed in Black and White and the paper is really cheap. Don't make a mistake like me buying same product for 90$ more. Again, the only difference between hardcover and softcover(international ver) is the price.