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glowingpython.blogspot.com | ||
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randalolson.com
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| | | | | Randy Olson shows how you can create your own traveling salesman portrait using Python. | |
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mika-s.github.io
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| | | | | One thing that can be hard to get right is the mapping from to radians to to radians. Or to to -180° to 180°. I've been unable to find information about it with Google (except for the functions that comes with Matlab), so I decided to share a function I've made that does the transformation. In C#: void TransformToPipi(double inputAngle, out double outputAngle, out int revolutions) { revolutions = (int)((inputAngle + Math.Sign(inputAngle) * Math.PI) / (2 * Math.PI)); outputAngle = (inputAngle + Math.Sign(inputAngle) * Math.PI) % (2 * Math.PI) - (Math.Sign(Math.Sign(inputAngle) + 2 * (Math.Sign(Math.Abs(((inputAngle + Math.PI) % (2 * Math.PI)) / (2 * Math.PI))) - 1))) * Math.PI; } The function takes an angle in radians as input and outputs an angle between and... | |
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gist.github.com
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| | | | | Implementing a Network-based Model of Epilepsy with Numpy and Numba. Code for https://danielegrattarola.github.io/posts/2019-10-03/epilepsy-model.html - eeg_generator_numba.py | |
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blog.fastforwardlabs.com
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| | | By Chris and Melanie. The machine learning life cycle is more than data + model = API. We know there is a wealth of subtlety and finesse involved in data cleaning and feature engineering. In the same vein, there is more to model-building than feeding data in and reading off a prediction. ML model building requires thoughtfulness both in terms of which metric to optimize for a given problem, and how best to optimize your model for that metric! | ||