wavded

iandanforth

#############################################################################
# Full Imports

from __future__ import division
import math
import random

"""
This is a pure Python implementation of the K-means Clustering algorithmn. The
original can be found here:

sloria

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

• "Build tools for others that you want to be built for you." - Kenneth Reitz
• "Simplicity is alway better than functionality." - Pieter Hintjens

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

lukas-h

Markdown License badges

Collection of License badges for your Project's README file.
This list includes the most common open source and open data licenses.
Easily copy and paste the code under the badges into your Markdown files.

Notes

• The badges do not fully replace the license informations for your projects, they are only emblems for the README, that the user can see the License at first glance.

Translations: (No guarantee that the translations are up-to-date)

• 🇫🇷 Cette liste en français

MariadeAnton

Travis CI - GitHub Satellite 2019

Menu

• Why

• Getting up and running

crittermike

# One liner
wget --recursive --page-requisites --adjust-extension --span-hosts --convert-links --restrict-file-names=windows --domains yoursite.com --no-parent yoursite.com

# Explained
wget \
     --recursive \ # Download the whole site.
     --page-requisites \ # Get all assets/elements (CSS/JS/images).
     --adjust-extension \ # Save files with .html on the end.
     --span-hosts \ # Include necessary assets from offsite as well.
     --convert-links \ # Update links to still work in the static version.

reecestart

import time
import boto3
import pprint

# setup pprint
pp = pprint.PrettyPrinter(indent=1)

# define the connection

client = boto3.client('organizations')

benoitdescamps

class XGBQuantile(XGBRegressor):
  def __init__(self,quant_alpha=0.95,quant_delta = 1.0,quant_thres=1.0,quant_var =1.0,base_score=0.5, booster='gbtree', colsample_bylevel=1,
                colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,max_depth=3, min_child_weight=1, missing=None, n_estimators=100,
                n_jobs=1, nthread=None, objective='reg:linear', random_state=0,reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,silent=True, subsample=1):
    self.quant_alpha = quant_alpha
    self.quant_delta = quant_delta
    self.quant_thres = quant_thres
    self.quant_var = quant_var
    
    super().__init__(base_score=base_score, booster=booster, colsample_bylevel=colsample_bylevel,

abdallahokasha

Install Robo3t On Ubuntu 18.04

Download the package form Robo3t or using wget

wget https://download.robomongo.org/1.2.1/linux/robo3t-1.2.1-linux-x86_64-3e50a65.tar.gz

Extract here using

tar -xvzf robo3t-1.2.1-linux-x86_64-3e50a65.tar.gz