Machine learning

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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System information

TensorFlow version: 1.13.1
Doc Link: https://www.tensorflow.org/api_docs/python/tf/cus

@fchollet

(e.g. for links and images), because some of these examples are now being rendered in the docs.

Added by @fchollet in requests for contributions.

@ngimel

>>> a = torch.randn(3,2,0,2)
>>> torch.flip(a, dims=())
tensor([], size=(3, 2, 0, 2))
>>> b = a.cuda()
>>> torch.flip(b, dims=())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: flip dims size out of range, got flip dims size=0

cc @ngimel @mruberry @rgommers @heitorschueroff

Describe the bug

In grid_to_graph, you expect the vertices to correspond to the implicit order defined by the mask. This is not always the case, due to the occurrence of isolated vertices that are dismissed in the reindexing of the vertices.

Steps/Code to Reproduce

import numpy as np
from sklearn.feature_extraction import grid_to_graph

mask = np.zeros((2, 3)).ast

Reference: JuliaLang/julia#38892 (comment)

We accidentally exported HTML and we should warn users to avoid them.

Currently many more Python projects like dask and optuna are using Python type hints. With the Python package of xgboost gaining more and more features, we should also adopt mypy as a safe guard against some type errors and for better code documentation.

Dec	JAN	Feb
	03
2020	2021	2022

Machine learning

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Steps/Code to Reproduce

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