Showing 4 open source projects for "yolov4.weights"

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    ThetaGang

    ThetaGang

    ThetaGang is an IBKR bot for collecting money

    ...This strategy reduces risk, but may also limit gains from big market swings. By reducing risk, one can increase leverage. ThetaGang will try to acquire your desired allocation of each stock or ETF according to the weights you specify in the config. To acquire the positions, the script will write puts when conditions are met.
    Downloads: 9 This Week
    Last Update:
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  • 2
    wger

    wger

    Self hosted FLOSS fitness/workout, nutrition and weight tracker

    ...Create your personal diet plan by creating as many meals with as many different ingredients as you need. The application will calculate the nutritional values ​​(total energy, proteins, carbohydrates, etc.) of the entire plan and of each of the meals. Enter the weights and reps you've done for each exercise to generate diagrams that let you see at a glance how well you're doing. Of course, the raw numbers are still accessible.
    Downloads: 6 This Week
    Last Update:
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  • 3
    PyTorch SimCLR

    PyTorch SimCLR

    PyTorch implementation of SimCLR: A Simple Framework

    ...And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the models’ pre-trained weights, append a new classifier layer on top of it, and retrain the network. This is called transfer learning, and is one of the most used techniques in CV. Aside from a few tricks when performing fine-tuning (if the case), it has been shown (many times) that if training for a new task, models initialized with pre-trained weights tend to learn faster and be more accurate then training from scratch using random initialization.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
    Downloads: 0 This Week
    Last Update:
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