This Pull Request is for HacktoberFest 2020

Description of Change

Checklist

• Added description

I'm using mxnet to do some work, but there is nothing when I search the mxnet trial and example.

Description of Change

References

Checklist

Describe the bug
Integer columns that are enclosed in quotes are not correctly inferred as integer columns.

Steps/Code to reproduce bug

import cudf
import pandas as pd
from io import StringIO
from cudf.tests.utils import assert_eq

buffer = '"intcol","stringcol"\n"1","some string"\n"2","some other string"'
pd_df = pd.read_csv(StringIO(buffer))
cu_df = cudf.read_csv(String

Hello everyone,

First of all, I want to take a moment to thank all contributors and people who supported this project in any way ;) you are awesome!

Due to my actual schedule, I'm very busy and I will not find much time to work fully (100%) on my open-source projects in the meantime.

I would like this project to continue improving, so I would be accepting maintainer(s) that would help mo

Report needed documentation

Report needed documentation
While the estimator guide offers a great breakdown of how to use many of the tools in api_context_managers.py, it would be helpful to have information right in the docstring during development to more easily understand what is actually going on in each of the provided functions/classes/methods. This is particularly important for

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/

Our xgboost models use the binary:logistic' objective function, however the m2cgen converted version of the models return raw scores instead of the transformed scores.

This is fine as long as the user knows this is happening! I didn't, so it took a while to figure out what was going on. I'm wondering if perhaps a useful warning could be raised for users to alert them of this issue? A warning

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually