TF-72a v2.2.2 AAX VST3 x64 WiN-R2R
December 15th, 2024 ⚡
Categories:
AAX, VST3, WiNDOWS, x64
TF-72a v2.2.2 WiN
Team R2R | 18 September 2024 | 51.5 MB
Introducing the “TF-72a” – a cutting-edge audio plugin meticulously crafted through the revolutionary power of Neural Networks and Deep Learning. This plugin is a faithful emulation of the legendary Vintage German tube preamp, an iconic piece of German engineering that graced some of the most renowned recording studios of yesteryears. Whether you’re tracking vocals, guitars, drums, or any other instrument, this plugin brings a touch of history and a dose of analog charm to your digital audio workstation. Unlock the secrets of the past and add a timeless sheen to your modern productions with the TF-72a – where the art of yesterday meets the science of tomorrow.
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Viewed 51044 By Music Producers & DJ´s.

Tags:
AAX, Deep Learning, Deep Learning Models, Networks, Neural, Neural Networks, Preamp, R2R, TF-72a, Tube, Vintage PreAMP, Vintage Tube, VST3, WiN, x64

Audio Classification Using Convolutional Neural Net TUTORiAL
August 29th, 2024 ⚡
Categories:
TUTORiALS
Audio Classification Neural Net
P2P | 29 August 2024 | 4.44 GB
This course is designed to provide a real understanding of handling audio files in machine learning. This course will give you a complete track record of processing audio files from A to Z using Python. This course will explain how to use Convolutional Neural Networks to generate an H5 AI model for audio classification purposes. This course gives you a complete understanding of Raspberry Pi 5 assembly, programming, AI Model deployment, and prediction of audio files. We will learn how to identify audio environments for machine-learning purposes. We will learn how to record audio files and slice them into clips of positive and negative types. How to process the raw audio clips and inject the “keyword” to be detected by the neural network. Apply clip labeling, clip slicing, and clip batching for the preparation of feeding audio clips to the Neural Net. Apply the required stages (load, time domain, frequency domain, spectrogram, and resize) to process raw audio clips for prediction use. Use Python programming to generate an H5 AI model for audio prediction purposes. Deploy and run the H5 AI model inside the Raspberry Pi 5 to control the movement of the servo motor with audio order. Testing the model with a real-time audio prediction process.
Buy/Download ✅

Viewed 12259 By Music Producers & DJ´s.

Tags:
Audio Classification, Classification, Net, Networks, Neural, Neural Net, Neural Networks

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TF-72a v2.2.2 WiN

Team R2R | 18 September 2024 | 51.5 MB

Audio Classification Neural Net

P2P | 29 August 2024 | 4.44 GB

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