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sebastianraschka.com | ||
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datascience.blog.wzb.eu
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| | | | | Modern computers are equipped with processors that allow fast parallel computation at several levels: Vector or array operations, which allow to execute similar operations simultaneously on a bunch... | |
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tothepoles.co.uk
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| | | | | There is a Jupyter Notebook accompanying this post HERE. NumPy is a Python package built around the concept of ndarrays (n-dimensional arrays) along with a suite of efficient functions for applying operations over those arrays. Many of the other important packages for data scientists are built on top of NumPy (e.g. Pandas, scikit-learn). In the... | |
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hadrienj.github.io
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| | | | | This introduction to scalars, vectors, matrices and tensors presents Python/Numpy code and drawings to build a better intuition behind these linear algebra b... | |
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vxlabs.com
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| | | LTTB, or Largest-Triangle-Three-Buckets, is a fantastic little algorithm that you can use for the visual downsampling of timeseries data. Let's say your user is viewing a line chart of some timeseries data. The time-period they have selected contains 50000 points, but their display is only 4K so they have a maximum of 3840 pixels available horizontally. With LTTB, we can automatically select the 3840 or fewer points from those 50000 points that will produce a line graph which is visually very similar to what they would see if they were to try and render all 50000 points. | ||
