The rapid advancement in the theoretical understanding of statistical and machine learning methods for semisupervised learning has made it difficult for nonspecialists to keep up to date in the field. Providing a broad, accessible treatment of the theory as well as linguistic applications, Semisuper
Semisupervised Learning for Computational Linguistics (Chapman & Hall/CRC Computer Science & Data Analysis)
β Scribed by Steven Abney
- Publisher
- Chapman and Hall/CRC
- Year
- 2007
- Tongue
- English
- Leaves
- 322
- Series
- Chapman & Hall/CRC Computer Science & Data Analysis
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
We're finally getting to the point where Computational Linguistics will start to see their titles in the titles. In the past one would have to piggyback off of another discipline to get the information they needed. This book is a must for anyone learning anything statistical in the NLP field. I took a class which covered nearly all of the topics in this book just months before the book came out. I struggled through some of the concepts and spent many a sleepless night going over an academic paper at least one more time getting those concepts down. On the last day of class the professor suggested this new title. I went and bought and most of the hard stuff I had struggled with solidified in my mind. A great feeling! I wish it was the textbook.
About the book itself; it does assume the reader is pretty math savvy. Some sections claim they are not breaking down a proof even though the only thing on the page are equations. But on the flip side, Abney does a fantastic job of grounding the terminology before launching into that. The first few chapters are very informative and patient with the reader. It is also excellent if you just need a refresher on any of these topics.
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