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

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

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