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Xbar is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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xdg-ninja is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Xplr is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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xremap is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Yabai is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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yarr is an open source project with code, documentation, and setup resources for RSS and feeds.
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Yattee is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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yet another bench script is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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You Don't Need GUI is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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YouTube-Viewer is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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ytermusic is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Yubikey Full Disk Encryption is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Zap is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Zapzap is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Zenith is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Zincsearch is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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Zoxide is an open source Linux, macOS, or Unix resource with code, tools, or setup notes.
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↗ external - Open-source agent that operates a real browser.
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Notebooks and code for the book "Introduction to Machine Learning with Python".
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Generate and download e-books from online sources.
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Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
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This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
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a single-user bookmarking website designed to live on the Fediverse
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Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media.