• MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • $300 in Free Credit Towards Top Cloud Services Icon
    $300 in Free Credit Towards Top Cloud Services

    Build VMs, containers, AI, databases, storage—all in one place.

    Start your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
    Get Started
  • 1
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    ...Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device.
    Downloads: 5 This Week
    Last Update:
    See Project
  • 2
    Orion

    Orion

    A machine learning library for detecting anomalies in signals

    Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    PyTorch pretrained BigGAN

    PyTorch pretrained BigGAN

    PyTorch implementation of BigGAN with pretrained weights

    An op-for-op PyTorch reimplementation of DeepMind's BigGAN model with the pre-trained weights from DeepMind. This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB