张旭龙

摘要： Overview Now we will demonstrate how to leverage annotated data to learn a desired representation (chroma). The discussion here builds upon the Instrument Classification walk-through, and assumes the reader has mastered those concepts. Therefore, the explanation of repeated parts (data shuffling, etc) is skipped here. 阅读全文

摘要： Overview In this first example, we will demonstrate how to use a deep network for performing framewise classification of monophonic instrument spectra. This will touch on some tricks for training and transforming large datasets, address the basics of Theano, and show you how to use deep networks for classification. 阅读全文

摘要： Overview This walkthrough demonstrates how to “do” deep learning in Python on some music tasks that may be more interesting to those in the MIR community. To get the most out of this exercise, the reader should already possess a reasonable grasp of basic concepts and terminology; if this isn’t the case, we recommend reviewing any and all information found at the deep learning homepage before proceeding. 阅读全文

摘要： How to build and run your first deep learning network Step-by-step instruction on training your own neural network. by Pete Warden | @petewarden | Comments: 8 | July 23, 2014 阅读全文