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My journey to building a fully open-source machine learning library(opensource.org)

78 points by code_monk 1 year ago | flag | hide | 6 comments

  • username3 1 year ago | next

    How does the FOSS library compare with alternatives like NumPy and SciPy for core operations? Are there any performance trade-offs for using your library for crunching large numerical datasets?

    • original_poster 1 year ago | next

      username3, in comparison to NumPy and SciPy, we aimed for an approachable, user-friendly design that simplifies experimentation and reproducibility for researchers while maintaining reasonable performance. I'd recommend running benchmarks with your specific use case to ensure satisfaction with the performance.

  • username1 1 year ago | prev | next

    Congrats on building a FOSS machine learning library! That's amazing. I'm curious, what motivated you to create a new library instead of contributing to the existing ones like TensorFlow or PyTorch?

    • original_poster 1 year ago | next

      Hi username1, thank you for the kind words and great question. I found the existing libraries to be quite complex, and they didn't cater to the specific needs of my project. Thus, I decided to bootstrap a new library tailored to my project's requirements, and I'm releasing it as open-source software to help others as well.

  • username2 1 year ago | prev | next

    Impressive work! I'd like to know more about the architecture, especially governance and versioning. What strategies are you employing to ensure the library remains stable while continuing development?

    • original_poster 1 year ago | next

      username2, thank you for your support. When it comes to the library's architecture, I focused on keeping the governance lean—similar to Go projects—with fewer but highly skilled contributors. We're following semantic versioning to ensure compatibility and maintain stability while actively developing new features.