legendof-selda

name: Publish docs via GitHub Pages
# syncs your mkdocs markdown files with azure devops wiki.
# NOTE: this doesn't work with automated markdown files which maybe generated in your case
# this also doesn't deal with ordering

on:
  push:
    branches:
      - develop
  workflow_dispatch:

tafaust

import random

import click
import uvicorn
from fastapi import FastAPI, APIRouter, Depends, Request


# Service
class MySingletonService:
    def __init__(self):

scottrigby

Demo: Flux Helm Operator -> Controller Migration

1. Create local cluster

   kind create cluster

2. Barebones flux2 install for demo

noelbundick

# We set an environment variable in this phase so it gets picked up by pip, but we don't want to bake secrets into our container image
FROM python:3.6-alpine AS builder

ARG INDEX_URL
ENV PIP_EXTRA_INDEX_URL=$INDEX_URL

COPY requirements.txt .

RUN pip install -U pip \
    && pip install --user -r requirements.txt

jjstill

# Starting minikube with 8Gb of memory and 3 CPUs
minikube --memory 8192 --cpus 3 start

# Creating separate Namespace for Spark driver and executor pods
kubectl create namespace spark

# Creating ServiceAccount and ClusterRoleBinding for Spark 
kubectl create serviceaccount spark-serviceaccount --namespace spark
kubectl create clusterrolebinding spark-rolebinding --clusterrole=edit --serviceaccount=spark:spark-serviceaccount --namespace=spark

swalkinshaw

Moved to Shopify/graphql-design-tutorial

amberjrivera

If You've Never Used Sklearn's Pipeline Constructor...You're Doing It Wrong

How To Use sklearn Pipelines, FeatureUnions, and GridSearchCV With Your Own Transformers

By Emily Gill and Amber Rivera

What's a Pipeline and Why Use One?

The Pipeline constructor from sklearn allows you to chain transformers and estimators together into a sequence that functions as one cohesive unit. For example, if your model involves feature selection, standardization, and then regression, those three steps, each as it's own class, could be encapsulated together via Pipeline.

Benefits: readability, reusability and easier experimentation.