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Ian H. Witten, Alistair Moffat, Timothy C. Bell
In this fully updated second edition of the highly acclaimed Managing Gigabytes, authors Witten, Moffat, and Bell continue to provide unparalleled coverage of state-of-the-art techniques for compressing and indexing data. Whatever your field, if you work with large quantities of information, this book is essential reading--an authoritative theoretical resource and a practical guide to meeting the toughest storage and access challenges. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries. It also details dozens of powerful techniques supported by mg, the authors' own system for compressing, storing, and retrieving text, images, and textual images. mg's source code is freely available on the Web. * Up-to-date coverage of new text compression algorithms such as block sorting, approximate arithmetic coding, and fat Huffman coding * New sections on content-based index compression and distributed querying, with 2 new data structures for fast indexing * New coverage of image coding, including descriptions of de facto standards in use on the Web (GIF and PNG), information on CALIC, the new proposed JPEG Lossless standard, and JBIG2 * New information on the Internet and WWW, digital libraries, web search engines, and agent-based retrieval * Accompanied by a public domain system called MG which is a fully worked-out operational example of the advanced techniques developed and explained in the book * New appendix on an existing digital library system that uses the MG software
Raul Garreta, Guillermo Moncecchi
The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous experience with machine-learning algorithms is required.