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-[// Algorithms](#-algorithms)
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-[// Plotting and Visualization](#-plotting-and-visualization)
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-[// Benchmarks](#-benchmarks)
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-[// Python and "Data Science"](#-python-and-data-science)
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-[// Other](#-other)
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-[// Useful scripts and snippets](#-useful-scripts-and-snippets)
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-[// Links](#-links)
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- Preparing Plots for Publication [[IPython nb](http://nbviewer.ipython.org/github/rasbt/matplotlib-gallery/blob/master/ipynb/publication.ipynb)]
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<br>
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###// Benchmarks
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[[back to top](#a-collection-of-useful-scripts-tutorials-and-other-python-related-things)]
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*The benchmark category has been moved to a separate GitHub repository [One-Python-benchmark-per-day](https://github.com/rasbt/One-Python-benchmark-per-day)*
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**Featured articles**:
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- (C)Python compilers - Cython vs. Numba vs. Parakeet [[IPython nb](http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day4_2_cython_numba_parakeet.ipynb)]
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- Just-in-time compilers for NumPy array expressions [[IPython nb](http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day7_2_jit_numpy.ipynb)]
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- Cython - Bridging the gap between Python and Fortran [[IPython nb](http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day10_fortran_lstsqr.ipynb)]
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- Parallel processing via the multiprocessing module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/multiprocessing_intro.ipynb)]
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- Vectorizing a classic for-loop in NumPy [[IPython nb](http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day16_numpy_vectorization.ipynb)]
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