Uploaded February 2020 | Updated September 2026, 2 weeks ago
In this video, you'll learn how to implement a Convolutional Neural Network (CNN) in TensorFlow. As a use case, we'll implement a music genre classifier. You'll also learn about cross-validation and how to perform inference in TensorFlow.
Code:
github.com/musikalkemist/DeepLearningForAudioWithPython/tree/master/16-%20How%20to%20implement%20a%20CNN%20for%20music%20genre%20classification/code
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In this video, you'll learn how to implement a Convolutional Neural Network (CNN) in TensorFlow. As a use case, we'll implement a music genre classifier. You'll also learn about cross-validation and how to perform inference in TensorFlow.
Code:
github.com/musikalkemist/DeepLearningForAudioWithPython/tree/master/16-%20How%20to%20implement%20a%20CNN%20for%20music%20genre%20classification/code
Join The Sound Of AI Slack community:
valeriovelardo.com/the-sound-of-ai-community
Interested in hiring me as a consultant/freelancer?
valeriovelardo.com
Connect with Valerio on Linkedin:
linkedin.com/in/valeriovelardo
Follow Valerio on Twitter:
twitter.com/musikalkemist
![MusicLM Generates Music From Text [Paper Breakdown]](https://i.ytimg.com/vi/eaqO5uT0G9Q/mqdefault.jpg "MusicLM Generates Music From Text [Paper Breakdown]
MusicLM has taken the Music AI community by storm. The model published by Google is a step ahead towards text-based music generation in the audio realm. By leveraging a clever combination of deep learning base models, MusicLM generates convincing short music clips with good audio fidelity.
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MusicLM paper:
https://arxiv.org/abs/2301.11325
MusicLM demo:
https://google-research.github.io/seanet/musiclm/examples/
Music AI talent recruitment:
https://thesoundofai.com/
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https://thesoundofai.com/consulting.html
The Sound of AI Academy:
https://the-sound-of-ai-academy.teachable.com/
Advanced Python Programming:
https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming
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Content:
0:00 Intro
0:45 Text-to-music
2:15 MusicLM demo
3:31 Riffusion and Mubert AI
4:37 MusicLM architecture
6:08 Components overview
7:40 SoundStream
8:20 w2v-BERT
8:51 MuLan
10:51 Training
16:18 Inference
19:52 Experiments
21:52 Limitations
24:40 Thoughts on research procedure")
