joys021 Goto Github PK

ansible-playbooks

api_usage

A starter project to introduce students to using REST APIs

big_data_projects

bulls_cycle_website_design

The Bullscycle website has been created as part of DIS Assignment 3

cicd-pipeline-train-schedule-cd

Train Schedule sample app for Jenkins Pipelines CD exercises

cicd-pipeline-train-schedule-docker

Train Schedule sample app for Docker exercises

cicd-pipeline-train-schedule-gradle

Train Schedule sample app for Gradle exercises

cicd-pipeline-train-schedule-jenkins

Train Schedule sample app for Jenkins exercises

cicd-pipeline-train-schedule-pipelines

Train Schedule sample app for Jenkins Pipelines exercises

classsol1

cloud-management-reporting

cloudformation-deep-dive

Course files for CloudFormation Deep Dive

cloudformation_templates

content-aws-devops-pro-2020

Craig Accuri, 03-05-2020, AWS DevOPs Pro

content-intermediate-docker-quest

Travis' Docker Quest

content-kafka-deep-dive

Chad's Kafka Course - May 2019

course_gke_beginner_to_pro

crud_flaskapp_1

crud_flaskapp_2

data

dis_computationalthinking

disassignment1

ecommerce-data-analysis-and-product-recommendation-system

Abstract: For this project the dataset we’ve chosen is the dataset of a Brazilian Ecommerce website “OLIST”. The details which OLIST has provided us are 9 different datasets each detailing the customers, their geolocation, orders placed, orders sold, items available, payment methods used by customers, order reviews & order delivery information. The analysis on the dataset is done through various methods like recommendation systems based on carrying out predictive analytics on users’ preferences, predicting the future sales on the basis of purchase date & discovering unsatisfied customers prone to certain product categories, clustered the customers based on Recency, Frequency and Monetary value. The above analysis has been in carried out in Apache pyspark 2.4.1 on both Cloudera platform and on Data bricks cloud environment.

frank-kanes-taming-big-data-with-apache-spark-and-python

Frank Kane's Taming Big Data with Apache Spark and Python, published by Packt

githubpipelinewithaws

helm-charts

SeQura Helm Charts

house-prediction-pyspark

Predicting house prices using pyspark

imad-2016-app

kafka-tools

A collection of tools for working with Apache Kafka.

learning_mongo

Exercise files for the Learning Mongo course on Lynda