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**Featured articles**:
- (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)]
- 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)]
- 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)]
- Parallel processing via the multiprocessing module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/multiprocessing_intro.ipynb)]
- 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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**Featured articles**:
- Entry Point: Data - Using Python's sci-packages to prepare data for Machine Learning tasks and other data analyses [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/python_data_entry_point.ipynb)]
- About Feature Scaling: Standardization and Min-Max-Scaling (Normalization) [[IPython nb](http://nbviewer.ipython.org/github/rasbt/pattern_classification/blob/master/preprocessing/about_standardization_normalization.ipynb)]
- Principal Component Analysis (PCA) [[IPython nb](http://nbviewer.ipython.org/github/rasbt/pattern_classification/blob/master/dimensionality_reduction/projection/principal_component_analysis.ipynb)]
- Linear Discriminant Analysis (LDA) [[IPython nb](http://nbviewer.ipython.org/github/rasbt/pattern_classification/blob/master/dimensionality_reduction/projection/linear_discriminant_analysis.ipynb)]
- Kernel density estimation via the Parzen-window technique [[IPython nb](http://nbviewer.ipython.org/github/rasbt/pattern_classification/blob/master/parameter_estimation_techniques/parzen_window_technique.ipynb)]