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Ethan Manilow
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.gitignore

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# PyCharm
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.idea/*
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book/training/Al James - Schoolboy Facination_vocals.json
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book/training/AM Contra - Heart Peripheral_vocals.json
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book/training/Angels In Amplifiers - I'm Alright_vocals.json
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book/training/Arise - Run Run Run_vocals.json
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book/training/BKS - Bulldozer_vocals.json

book/appendix/acknowledgements.md

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### nussl
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- Fatemeh Pishdadia
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- Fatemeh Pishdadian
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- Nathan Shelly
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- Andreas Bugler
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- Bryan Pardo

book/training/intro.md

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Training deep nets for dummies
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==============================
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Intro
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=====
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Training deep networks in any field can be a challenging endeavor. It requires patience,
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luck, and a lot of debugging. The goal of this section is to provide an overview
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- Gradient-descent based optimization
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- Inputs and outputs for audio separation networks
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- The building blocks of modern deep nets for separation
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- Training a model with a straightforward script based on Scaper and nussl.
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- How to diagnose and fix common bugs
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As we proceed through this section, we will gradually build up a script that can be used

book/training/putting_it_all_together.ipynb

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