Pattern Recognition Primer by Karol Przystalski (.ePUB)+

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File Size: 56.9 MB

Pattern Recognition Primer by Karol Przystalski, Maciej J. Ogorzałek, Jan K. Argasiński, Wiesław Chmielnicki
Requirements: .ePUB, .PDF reader, 56.9 MB
Overview: This textbook provides semester-length coverage of pattern recognition/classification, accessible to everyone who would like to understand how pattern recognition and Machine Learning works. It explores the most commonly used classification methods in an intelligible way. Unlike other books available for this course, this one explains from top to bottom each method with all needed details. Every method described is explained with examples in Python. The presentation is designed to be highly accessible to students from a variety of disciplines, with no experience in Machine Learning. Each chapter contains easy to understand code samples, as well as exercises to consolidate and test knowledge. From a programming in Python perspective, there are two ways of training Machine Learning methods. The first is an iterative way in which we go through each element in a vector or matrix to calculate the expected result. This approach is based on many for or while loops. The second approach is based on libraries like NumPy that are adjusted and perform much better than any iterative implementation.
Genre: Non-Fiction > Tech & Devices

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