Showing 3 open source projects for "python 2"

View related business solutions
  • Earn up to 15% annual interest with Nexo. Icon
    Earn up to 15% annual interest with Nexo.

    More flexibility. More control.

    Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • Earn up to 15% annual interest with Nexo. Icon
    Earn up to 15% annual interest with Nexo.

    Access competitive interest rates on your digital assets.

    Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • 1
    Faker for Python

    Faker for Python

    Python package that generates fake data for you

    Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    FuseSoC

    FuseSoC

    Package manager and build abstraction tool for FPGA/ASIC development

    FuseSoC is a package manager and build abstraction tool for hardware description language (HDL) code, aimed at simplifying the development and reuse of IP cores. It provides a standardized way to describe, manage, and build hardware projects, facilitating collaboration and reducing duplication of effort in FPGA and ASIC development. ​
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    DeepCTR

    DeepCTR

    Package of deep-learning based CTR models

    DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB