Machines Books

I think you will find this an awesome book, as long as you know what to expect. Reiss focuses on external horn machines, and includes only a couple of pictures of the internal horn machines. If you are looking for a book with lots of details about Victrola models, this is not it.

That's not a problem if you are looking for repair information, since most wind-up machines share the same basic construction. Reiss is a great technical writer, giving you step-by-step instructions in nice readable English. He covers both mechanical repairs (such as rebuilding the reproducer or fixing a broken spring) and cosmetic repairs. I really liked his tips for cleaning the finish and repairing blemishes and dings.

In summary, if you own a talking machine and want to fix it or spruce it up, this book is a critical resource. If you are shopping for a Victrola, this is not the book for you. I take that back. I would have shopped much more intelligently for my first Victrola if I had read this book first. Just changed the rating from 4 to 5!

As the loving, devoted caretaker of two happily, healthily running Victrolas, I am constantly on the lookout for tips on how best to care for my babies (yes, that's how much I love them). For years it was a matter of word-of-mouth, hunting down collectors, antique dealers and little old men who worked on phonographs in their garages. And though these resources have been a boon throughout the years, I am so very happy to have found this wonderful book - now, I consider it's advice before looking outside of my handy capabilities.

Reiss' book focuses solely on vintage phonograph maintenance and restoration - none of the later electric models are mentioned, only the earlier, strictly acoustic machines are featured. Makes and models of all sorts are covered, and instructions are provided (with visual aids - hooray) for mechanical work spanning from the most basic fix-up to complete overhaul. Broken mainspring? Grinding motor? Uneven speed? The repair methods are all at your fingertips with this book. Reiss tells of his experiences in starting out with "basket cases", and how he personally worked on them until full restoration had been achieved. As well, cosmetic issues are addressed, from refinishing cabinets, replacing lost trimwork, and selection of reproduction decals - it's all here.

Most importantly, Reiss writes in an easily understandable style, and sprinkles humor throughout. As well, he is unafraid of pointing out when a repair is best handled by a professional. The book will be a true joy and fascinating read for any lover of phonographs - and truly indispensible for any owner of one.

My 21 year old niece had this book and I was fascinated by the overabundance of great recipes. Plenty of great pictures of different breads from many, many areas and cultures of the world. You get information on when these breads are eaten and sometimes a little history of the bread. In depth info. on bread ingredients and pans and methods of mixing, kneading and baking. This is the most comprehensive bread book I have come across. My niece has been baking breads from this book almost daily. I had to order one for myself and will very likely order one for my mother. I have been using a bread machine for various doughs for years and love it. This book actually inspires me to indulge in my love for cooking and make bread the old fashioned way also.

Professor George Edward Challenger is the lesser known creation of Sherlock Holmes' creator, Arthur Conan Doyle (1859-1930). Unlike the cool and calculating Homes, Challenger is irascible, domineering and extremely outspoken. In short, he is a lot of fun to read. However, unlike Holmes, Professor Challenger never caught on and as such only five Challenger stories were ever written. This book combines all five of the Professor Challenger stories together in one book:

The Lost World - originally published in 1912 - 5 stars - This is the greatest, and the best known of the Professor Challenger stories. Professor Challenger has heard of a plateau in South America where dinosaurs still roam, and he loses no time in setting up an expedition to this strange place. However, when the expedition finds itself marooned on the plateau, the team faces many dangers and adventures.

The Poison Belt - 1913 - 5 stars - Professor Challenger has learned that the Earth is moving towards a poisonous section of space, and has figured out a way that he can save a few members of the human race - the last people left on Earth!

The Land of Mist - 1926 - 1 star - The worst of the Professor Challenger stories, this one is really just a polemic, written to convince the reader of the wonder (or whatever) of Spiritualism. This story might have been what killed the series.

The Disintegration Machine - 1927 - 5 stars - A Latvian scientist has created a machine that can disintegrate matter, and reintegrate it again...or not. This is something that Professor Challenger must see for himself if he is to fully understand its ramifications.

When The World Screamed - 1928 - 5 stars - Professor Challenger is digging a well or mine of some sort in southern England, but what is he up to? It seems that the eccentric professor has a new theory - that the Earth is really a living creature!

Although more than a little dated, scientifically, I found these stories to be well written and quite exciting. (Well, four of the five that is.) They reflects a world that is now gone, but is quite interesting to read about. If you like adventure stories, then you will like this one. Read this book, and learn about A.C. Doyle's other hero!

This is the most thorough book on the subject I have ever seen. A very broad wealth of material is included. Contrary to what one sees in books on such specialized subjects, this one goes into the details. A must for compressor designers.

For the THEORETICAL COMPUTER SCIENTIST, calculability is the foundations that will lead to complexity considerations...For those liking a rigouros approach (for example with a mathematical background) , this book is just what they need...

MATHEMATICIANS should all find great pleasure in reading at least once in there life something about undecidable problems...(Yes there are some! ), and things such as: are real numbers just an illusion? etc...

People interested in the alternative "KLEEN FUNCTIONS" approach to calculability (instead of the classical TM approach or lambda calculus) will be delighted too...(Those accustumed with the TM approch will only like it more, but the book is absolutely complete in it's self...)

Table of Contents
PREFACE

INTRODUCTION AND BACKGROUND
LESS IS MORE
Huan Liu and Hiroshi Motoda
Background and Basics
Supervised, Unsupervised, and Semi-Supervised Feature Selection
Key Contributions and Organization of the Book
Looking Ahead

UNSUPERVISED FEATURE SELECTION
Jennifer G. Dy
Introduction
Clustering
Feature Selection
Feature Selection for Unlabeled Data
Local Approaches
Summary

RANDOMIZED FEATURE SELECTION
David J. Stracuzzi
Introduction
Types of Randomizations
Randomized Complexity Classes
Applying Randomization to Feature Selection
The Role of Heuristics
Examples of Randomized Selection Algorithms
Issues in Randomization
Summary

CAUSAL FEATURE SELECTION
Isabelle Guyon, Constantin Aliferis, and André Elisseeff
Introduction
Classical "Non-Causal" Feature Selection
The Concept of Causality
Feature Relevance in Bayesian Networks
Causal Discovery Algorithms
Examples of Applications
Summary, Conclusions, and Open Problems

EXTENDING FEATURE SELECTION
ACTIVE LEARNING OF FEATURE RELEVANCE
Emanuele Olivetti, Sriharsha Veeramachaneni, and Paolo Avesani
Introduction
Active Sampling for Feature Relevance Estimation
Derivation of the Sampling Benefit Function
Implementation of the Active Sampling Algorithm
Experiments
Conclusions and Future Work

A STUDY OF FEATURE EXTRACTION TECHNIQUES BASED ON DECISION BORDER ESTIMATE
Claudia Diamantini and Domenico Potena
Introduction
Feature Extraction Based on Decision Boundary
Generalities about Labeled Vector Quantizers
Feature Extraction Based on Vector Quantizers
Experiments
Conclusions

ENSEMBLE-BASED VARIABLE SELECTION USING INDEPENDENT PROBES
Eugene Tuv, Alexander Borisov, and Kari Torkkola
Introduction
Tree Ensemble Methods in Feature Ranking
The Algorithm: Ensemble-Based Ranking against Independent Probes
Experiments
Discussion

EFFICIENT INCREMENTAL-RANKED FEATURE SELECTION IN MASSIVE DATA
Roberto Ruiz, Jesús S. Aguilar-Ruiz, and José C. Riquelme
Introduction
Related Work
Preliminary Concepts
Incremental Performance over Ranking
Experimental Results
Conclusions

WEIGHTING AND LOCAL METHODS
NON-MYOPIC FEATURE QUALITY EVALUATION WITH (R)RELIEFF
Igor Kononenko and Marko Robnik Šikonja
Introduction
From Impurity to Relief
ReliefF for Classification and RReliefF for Regression
Extensions
Interpretation
Implementation Issues
Applications
Conclusion

WEIGHTING METHOD FOR FEATURE SELECTION IN K-MEANS
Joshua Zhexue Huang, Jun Xu, Michael Ng, and Yunming Ye
Introduction
Feature Weighting in k-Means
W-k-Means Clustering Algorithm
Feature Selection
Subspace Clustering with k-Means
Text Clustering
Related Work
Discussions

LOCAL FEATURE SELECTION FOR CLASSIFICATION
Carlotta Domeniconi and Dimitrios Gunopulos
Introduction
The Curse of Dimensionality
Adaptive Metric Techniques
Large Margin nearest Neighbor Classifiers
Experimental Comparisons
Conclusions

FEATURE WEIGHTING THROUGH LOCAL LEARNING
Yijun Sun
Introduction
Mathematical Interpretation of Relief
Iterative Relief Algorithm
Extension to Multiclass Problems
Online Learning
Computational Complexity
Experiments
Conclusion

TEXT CLASSIFICATION AND CLUSTERING
FEATURE SELECTION FOR TEXT CLASSIFICATION
George Forman
Introduction
Text Feature Generators
Feature Filtering for Classification
Practical and Scalable Computation
A Case Study
Conclusion and Future Work

A BAYESIAN FEATURE SELECTION SCORE BASED ON NAÏVE BAYES MODELS
Susana Eyheramendy and David Madigan
Introduction
Feature Selection Scores
Classification Algorithms
Experimental Settings and Results
Conclusion

PAIRWISE CONSTRAINTS-GUIDED DIMENSIONALITY REDUCTION
Wei Tang and Shi Zhong
Introduction
Pairwise Constraints-Guided Feature Projection
Pairwise Constraints-Guided Co-clustering
Experimental Studies
Conclusion and Future Work

AGGRESSIVE FEATURE SELECTION BY FEATURE RANKING
Masoud Makrehchi and Mohamed S. Kamel
Introduction
Feature Selection by Feature Ranking
Proposed Approach to Reducing Term Redundancy
Experimental Results
Summary

FEATURE SELECTION IN BIOINFORMATICS
FEATURE SELECTION FOR GENOMIC DATA ANALYSIS
Lei Yu
Introduction
Redundancy-Based Feature Selection
Empirical Study
Summary

A FEATURE GENERATION ALGORITHM WITH APPLICATIONS TO BIOLOGICAL SEQUENCE CLASSIFICATION
Rezarta Islamaj Dogan, Lise Getoor, and W. John Wilbur
Introduction
Splice-Site Prediction
Feature Generation Algorithm
Experiments and Discussion
Conclusions

AN ENSEMBLE METHOD FOR IDENTIFYING ROBUST FEATURES FOR BIOMARKER DISCOVERY
Diana Chan, Susan M. Bridges, and Shane C. Burgess
Introduction
Biomarker Discovery from Proteome Profiles
Challenges of Biomarker Identification
Ensemble Method for Feature Selection
Feature Selection Ensemble
Results and Discussion
Conclusion

MODEL BUILDING AND FEATURE SELECTION WITH GENOMIC DATA
Hui Zou and Trevor Hastie
Introduction
Ridge Regression, Lasso, and Bridge
Drawbacks of the Lasso
The Elastic Net
The Elastic-Net Penalized SVM
Sparse Eigen-Genes
Summary

INDEX

Chapter 4 of this book is the pot of gold: A concrete, detailed description of how the cerebral cortex works. Thinking relies upon an operation which could be called confabulation (in the chapter it is called concensus building). THIS IS NOT REASONING (at least in any classical sense). Yet, because the simple kind of knowledge used (antecedent support probabilities) is exhaustive, concensus building yields excellent conclusions. This cortical theory also shows why AI has failed: reasoning is too difficult and requires too much knowledge of an expensive type. Cortex gets by with a much simpler type of knowledge (which only concerns pairs of object and action attributes, not n-tuples) which, while it is needed in huge quantities, is easy to obtain. An implication of this corticl theory is that we can now proceed to develop successful AI by adopting this cortical design. The theory is illustrated by means of computer thinking experiments that yield compelling results (and which readers can replicate).

A very original and well-reasoned text. I'd like to thank Dr. Sproat for his contribution to the field. This is very fine fork.

This is an exclente reading about the computer control on the industry. Kletz has the hability to make the reading easy and comprehensive. I recommend that.