SeaLion
mlcourse.ai
| SeaLion | mlcourse.ai | |
|---|---|---|
| 4 | 85 | |
| 332 | 9,496 | |
| - | - | |
| 5.2 | 0.0 | |
| 7 months ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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SeaLion
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Cython, why should I care?
I was searching reddit earlier, for certain machine learning topics, and I came across a topic which looks like a showcase. By following the links leading to the repo, I found some .pyx and .pxd hybrid modules. I was always skeptical about taking the trouble of writing modules in this weird syntax, expecting promising performance gains. By searching cython projects on github, I found many others. It looks like some people found it interesting to adopt in their projects. What can you consider as valid use case(s) for cython? I mean if you're really that worried about performance, which you can't get using python, wouldn't it be wiser to use optimized C/C++ with possibly a python API?
- A Python ML framework that encourages learning ML concepts
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Machine Learning Library by 14-year old : SeaLion
We do that already inside of the source code. The ensemble learning classifier has a method in which you can train multiple models all at once in parallel and then get the best classifier on the dataset. You can check out the ensemble learning tutorials here : ensemble learning tutorial
mlcourse.ai
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