2 projects for "python feature selection" with 2 filters applied:

  • Personalized Text Messaging for Innovative Brands | Attentive Icon
    Personalized Text Messaging for Innovative Brands | Attentive

    Send smarter campaigns, see faster conversions, achieve higher ROI

    Reach your customers where they are—their phones. Attentive’s conversational commerce platform helps 8,000+ brands—from retail enterprises to e-commerce entrepreneurs—engage customers and drive billions in revenue via SMS marketing. We'll help you target the right audience for your messages, and measure your most important metrics to optimize your program. And with our flexible integrations, you can easily connect to the rest of your marketing stack, too. Learn more about our free 30-day trial.
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  • Hopted brings live data to your Google Sheets. Icon
    Hopted brings live data to your Google Sheets.

    Using spreadsheets can lead to a lot of manual work, outdated information and the risk of human error. So along came Hopted.

    Hopted links your Sheets to the business software you use daily — marketplaces, accounting, ad performance, CRM, ERP — you name it.
    Learn More
  • 1
    Detectron

    Detectron

    FAIR's research platform for object detection research

    Detectron is an object detection and instance segmentation research framework that popularized many modern detection models in a single, reproducible codebase. Built on Caffe2 with custom CUDA/C++ operators, it provided reference implementations for models like Faster R-CNN, Mask R-CNN, RetinaNet, and Feature Pyramid Networks. The framework emphasized a clean configuration system, strong baselines, and a “model zoo” so researchers could compare results under consistent settings. It includes...
    Downloads: 0 This Week
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  • 2
    R-FCN

    R-FCN

    R-FCN: Object Detection via Region-based Fully Convolutional Networks

    R-FCN (“Region-based Fully Convolutional Networks”) is an object detection framework that makes almost all computation fully convolutional and shared across the image, unlike prior region-based approaches (e.g. Faster R-CNN) which run per-region sub-networks. The repository provides an implementation (in Python) supporting end-to-end training and inference of R-FCN models on standard datasets. The authors propose position-sensitive score maps to reconcile the need for translation variance...
    Downloads: 0 This Week
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