Showing 6 open source projects for "sample size"

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  • 1
    Letterboxd Recommendations

    Letterboxd Recommendations

    Scraping publicly-accessible Letterboxd data for movie recommendations

    ...A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). All movies in the full dataset that the user has not rated are run through the model for predicted scores and the items with the top predicted scores are returned. Due to constraints in time and computing power, the maximum sample size that a user is allowed to select is 500,000 samples, though there are over five million ratings in the full dataset from the top 4000 Letterboxd users alone.
    Downloads: 0 This Week
    Last Update:
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  • 2
    MCPower

    MCPower

    MCPower — simple Monte Carlo power analysis for complex models

    ...It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. ...
    Downloads: 2 This Week
    Last Update:
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  • 3
    Keras TCN

    Keras TCN

    Keras Temporal Convolutional Network

    ...Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the maximum number of steps back in time from current sample at time T, that a filter from (block, layer, stack, TCN) can hit (effective history) + 1. ...
    Downloads: 0 This Week
    Last Update:
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  • 4
    HiFi-GAN

    HiFi-GAN

    Generative Adversarial Networks for Efficient and High Fidelity Speech

    HiFi-GAN is a GAN-based neural vocoder designed to generate high-fidelity speech waveforms from mel spectrograms with exceptional efficiency. It introduces a generator architecture tailored to model the periodic structure of speech and a set of discriminators that focus on different scales and periods of the waveform to better capture naturalness. The model targets a sweet spot between sample quality and generation speed, outperforming many previous GAN vocoders while being far faster than...
    Downloads: 0 This Week
    Last Update:
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  • 5
    LiVES

    LiVES

    LiVES is a Video Editing System. It is designed to be simple to use, y

    ...You can even record your performance in real time, and then edit it further or render it straight away. For the more technically minded, the application is frame and sample accurate, and it can be controlled remotely or scripted for use as a video server. And it supports all of the latest free standards.
    Downloads: 14 This Week
    Last Update:
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  • 6
    superboucle

    superboucle

    Loop based software with jack transport, record and midi controllable

    ...Which mean sample can start before next beat (useful for reversed sample). You can record loop of any size, adjust BPM, reverse, normalize samples, ... Typical usage : * You need to control jack transport with external midi device and want a button to jump to a specified location in song. * You have some instruments patterns but you have no idea of song structure
    Downloads: 3 This Week
    Last Update:
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