Showing 3 open source projects for "mix"

View related business solutions
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • Veeam Data Platform v13.1 - Get Your Free Trial Icon
    Veeam Data Platform v13.1 - Get Your Free Trial

    Secure by design, portable by default. Recover clean, fast, anywhere. Start a free trial.

    Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
    Try it Free
  • 1
    Audiomentations

    Audiomentations

    A Python library for audio data augmentation

    ...Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where 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. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    Robyn

    Robyn

    Experimental, AI/ML-powered and open sourced Marketing Mix Modeling

    Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. ...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 3
    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next