Showing posts with label prolog. Show all posts
Showing posts with label prolog. Show all posts

Practical Risk Assessment for Project Management Review

Practical Risk Assessment for Project Management
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Practical Risk Assessment for Project Management ReviewThe ideal audience for this book is relatively narrow, consisting of readers who meet the following two criteria: (1) new to risk management techniques, and (2) using Palisade @Risk. In fact, this book comes close to being a tutorial on using @Risk, which is a popular commercial product that works within Microsoft Excel and project management programs.
If you are new to advanced techniques in project risk management you'll like the way the author succinctly covers all of the key elements of project risk assessment, project finance forecasting, and simulation and modeling. Considering the complexity of the subject area, and the fact that both probability and simulation techniques are covered, the author does a remarkable job of conveying the wide range of topics in a scant 134 pages. I especially liked the generous use of graphs and examples, and the way each topic was broken down into easy-to-grasp facts and steps.
However, even without @Risk you can learn much about risk assessment from this book, including a refresher on probability distributions, how to perform an assessment using manual techniques, and modeling and simulation with an emphasis on Monte Carlo simulation.
The only problem I have with this book is that it's out of date with respect to @Risk, which has evolved into a much more capable tool since this book was first published 7 years ago. Since one of the this book's strengths is the way it teaches how to apply @Risk to real world project risk assessment, the fact that it's out of date with respect to the software version diminishes its value.Practical Risk Assessment for Project Management OverviewIn the estimating, planning and management of any project, large or small, an understanding of the impact of risk is critical. This book explains how the growing number of people choosing to or forced to organise their work as projects can make realistic assessments of the uncertainty affecting costs, timescale and revenue, before commitments are made. A clear analysis of the role of uncertainty is combined in this concise and practical handbook with simple, cost-effective techniques for measuring and modelling the overall risk to a project's budget and schedule. There is advice and help here for the whole project team, including project managers; bid managers; project sales professionals; planners; estimators; managers running a project-based business; and consultants and auditors advising a projects business. Drawn from the author's extensive experience on projects ranging in scale from a few man-months to hundreds of man-years, the book will beelevant to anyone involved in a project-based business. Examples are presented as simple models, built in spreadsheets using the @Risk software package. No more than basic knowledge of Lotus 1-2-3?? or Excel?? will be required by the reader.

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An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies) Review

An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies)
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An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies) ReviewThis book has the same scope as Speech and Language Processing (2nd Edition) (Prentice Hall Series in Artificial Intelligence), but that book flies too high over the details. This book does a good job of covering the details without getting lost in them. The author takes the approach of explaining a concept first with excellent illustrations, then explains the algorithm that implements the concept, then shows detailed code in either Prolog or PERL.
This is not to say you can pick up this book without the proper background and get much out of it. Language processing is a field requiring a good background in a number of fields including the theory of computation, linguistics, artificial intelligence, and information theory to name a few. You should be familiar with all of these fields before tackling the book, although the author does introduce these topics somewhat before digging into details.
One thing the author does not do much of is explain Prolog or PERL. He assumes you already know these languages, although there is an appendix at the back of the book covering Prolog. Prolog is a difficult language to learn and is not at all intuitive. However, it is an excellent choice for coding up many algorithms concerning artificial intelligence. Thus, although I do not argue with the author's choice of language, I do recommend that you become fluent in Prolog before you read this book.
I used to recommend Jurafsky and Martin for people starting out learning language processing, but now I think I can recommend this book for not only the big picture but the details of this interesting field as well.An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies) OverviewThis book teaches the principles of natural language processing and covers linguistics issues. It also details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques. A key feature of the book is the author's hands-on approach throughout, with extensive exercises, sample code in Prolog and Perl, and a detailed introduction to Prolog. The book is suitable for researchers and students of natural language processing and computational linguistics.

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