- Numpy's greatest feature: broadcasting. It is more addictive than uncut coke. It allows easy handling of lots of data in a scalable way. Every matrix-supporting language should have this. http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html 6 comments programming
Linking pages
- PEP 465 – A dedicated infix operator for matrix multiplication | peps.python.org http://www.python.org/dev/peps/pep-0465/ 41 comments
- Python Numpy Tutorial (with Jupyter and Colab) http://cs231n.github.io/python-numpy-tutorial/ 28 comments
- gnuplotlib/guide.org at master · dkogan/gnuplotlib · GitHub https://github.com/dkogan/gnuplotlib/blob/master/guide/guide.org 2 comments
- Make your Python functions 10x faster | by Rushabh Vasani | Towards Data Science https://towardsdatascience.com/make-your-python-functions-10x-faster-142ab40b31a7 2 comments
- Implementing Naive Bayes in Python | sidsite https://sidsite.com/posts/implementing-naive-bayes-in-python/ 0 comments
- NumPy mgrid vs. meshgrid | Louis Tiao http://louistiao.me/posts/numpy-mgrid-vs-meshgrid/ 0 comments
- GitHub - tensorflow/probability: Probabilistic reasoning and statistical analysis in TensorFlow https://github.com/tensorflow/probability 0 comments
- Solving the Shove/fold Game with TensorFlow http://willtipton.com/coding/poker/2016/03/06/shove-fold-with-tensorflow.html 0 comments
- NumPy Tutorial: Data Analysis with Python – Dataquest https://www.dataquest.io/blog/numpy-tutorial-python/ 0 comments
- GitHub - dkogan/numpysane: more-reasonable core functionality for numpy https://github.com/dkogan/numpysane 0 comments
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