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<title><![CDATA[Comentarios al libro: MACHINE LEARNING FOR AUDIO, IMAGE AND VIDEO ANALYSIS]]></title>
<link><![CDATA[https://www.biblioeteca.com/biblioeteca.web/titulo/machine-learning-for-audio%2C-image-and-video-analysis]]></link>
<description><![CDATA[This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book.<br>Divided into three main parts, <i>From Perception to Computation</i> introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, <i>Machine Learning</i> includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part <i>Applications</i> shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data.<p><i>Machine Learning for Audio, Image and Video Analysis</i> is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.]]></description>
<lastBuildDate>Wed, 02 Sep 2026 00:52:15 +0000</lastBuildDate>
<language>es</language>
<copyright>Copyright 202 6BiblioEteca Technologies SL</copyright>

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