Vectorized version of gradient descent.

theta = theta * reg_param - alpha * (1 / num_examples) * (delta.T @ self.data).T

We should NOT regularize the parameter theta_zero.

theta[0] = theta[0] - alpha * (1 / num_examples) * (self.data[:, 0].T @ delta).T

the first code line ,theta include theta[0].
so I think can write like this:
theta[0] -= alpha * (1 / num_examples) * (self.data[:, 0].

My feature request is to include an option on a button made from choice skill, to redirect a link to an external url...

Here's a detailed explanation including screenshots

https://help.botpress.io/t/how-to-redirect-to-an-external-url-while-using-a-button-made-in-choice-skill/1791

This option will be really beneficial using choice skill buttons since at the moment, you can only add an ext

it is really great code , only how to run it
MLAlgorithms/mla/fm.py
may you add example , as you did for other models?

Is your feature request related to a problem? Please describe.
According to the Arrow spec:

Bitmaps are to be initialized to be all unset at allocation time (this includes padding).

This would imply that bits outside the range [0, size) should always be zero. However, in cuDF/libcudf, we take a more conservative approach and say that bits outside [0,size) are undefined in order to a

Hello,
I am building a QGIS plugin and would like to add hdbscan in methods. But when I import with OSGEO4W shell it failed at this line:
File "C:\OSGeo4W\apps\Python37\lib\site-packages\hdbscan-0.8.22-py3.7-win32.egg\hdbscan_init_.py", line 1, in
from .hdbscan_ import HDBSCAN, hdbscan
File "C:\OSGeo4W\apps\Python37\lib\site-packages\hdbscan-0.8.22-py3.7-win32.egg\hdbscan\h

I'm sorry if I missed this functionality, but CLI version hasn't it for sure (I saw the related code only in generate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.

Of course, piping is a solution, but not for development in Jupyter Notebook, for example.

Currently, they are just all over the place! I propose the following rule-of-thumb:

1. If a header file contains cuda kernels and/or device methods, then it should be a .cuh.
2. Else, it should be a .hpp (if the current header file is already named as a .h, feel free to leave it as it is, in order to minimize the amount of ripple changes this will cause).
3. If a header file is used to de

Describe the bug

In StellarGraph, some algorithms are in demo notebooks or scripts, without being listed in our main documentation. This could mean that a user reading our docs thinks they're not supported in StellarGraph.

Currently tslearn/tests/test_estimators.py redefine a custom check_estimator and then monkeypatch some of the tests in sklearn.utils.estimator_checks to work with time series data.

In the latest version scikit-learn introduced parametrize_with_checks which should allow to simplify this quite a bit https://scikit-learn.org/stable/developers/develop.html#rolling-your-own-estimator (e.g. a

• The median heuristic function utils.medianHeuristic is missing in the pytorch branch. Please copy it to edgeml_pytorch.utils.
• It is being called from here when you run the example. That is