SeaLion
susi
| SeaLion | susi | |
|---|---|---|
| 4 | 1 | |
| 333 | 102 | |
| - | - | |
| 5.2 | 6.5 | |
| 7 months ago | about 2 months ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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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
susi
What are some alternatives?
scikit-learn - scikit-learn: machine learning in Python
minisom - :red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
mlcourse.ai - Open Machine Learning Course
alibi-detect - Algorithms for outlier, adversarial and drift detection
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
trackball-python - Python library for the Pimoroni Track Ball Breakout
tinyHTTPie - TinyHTTPie is the Product of the Multi-Part Series "The Evolution of a Script".
somoclu - Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
sparse-som - Efficient Self-Organizing Map for Sparse Data
som-tsp - Solving the Traveling Salesman Problem using Self-Organizing Maps