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    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    ... science, empowering data scientist to quickly understand and automatically detect silent model failure. By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance.
    Downloads: 0 This Week
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    Audiomentations

    Audiomentations

    A Python library for audio data augmentation

    ... background noise is present. A folder of (background noise) sounds to be mixed in must be specified. These sounds should ideally be at least as long as the input sounds to be transformed. Otherwise, the background sound will be repeated, which may sound unnatural. Note that the gain of the added noise is relative to the amount of signal in the input. This implies that if the input is completely silent, no noise will be added.
    Downloads: 0 This Week
    Last Update:
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