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scikit-learn vs SciPy: What are the differences?
Developers describe scikit-learn as "Easy-to-use and general-purpose machine learning in Python". scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license. On the other hand, SciPy is detailed as "Scientific Computing Tools for Python". Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
scikit-learn can be classified as a tool in the "Machine Learning Tools" category, while SciPy is grouped under "Data Science Tools".
scikit-learn and SciPy are both open source tools. It seems that scikit-learn with 36K GitHub stars and 17.6K forks on GitHub has more adoption than SciPy with 6.01K GitHub stars and 2.85K GitHub forks.
According to the StackShare community, scikit-learn has a broader approval, being mentioned in 71 company stacks & 40 developers stacks; compared to SciPy, which is listed in 12 company stacks and 4 developer stacks.
Pros of scikit-learn
- Scientific computing23
- Easy18
Pros of SciPy
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Cons of scikit-learn
- Limited2
Cons of SciPy
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What is scikit-learn?
What is SciPy?
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