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airflow

This project will introduce you to the core concepts of Apache Airflow. To complete the project, you will need to create your own custom operators to perform tasks such as staging the data, filling the data warehouse, and running checks on the data as the final step.

analyse_ab_test_result

bikeshare_datamining

n this project, you will make use of Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. You will write code to import the data and answer interesting questions about it by computing descriptive statistics. You will also write a script that takes in raw input to create an interactive experience in the terminal to present these statistics.

cloud_data_warehouse_aws

cv_ps_etc

My CV/Resume

data-engineering-nanodegree

notebooks produced throughout the Udacity's Nanodegree Data Engineering Course

data_engineering_capstone

data_lake

Udacity Data Lake practice

data_lakes_with_spark

data_modeling_with_postgres

well, looks like sometimes I submit my work by other email address, it may not show on my github report, but I will remind my self to use correct email address at the future. cheers.

data_streaming

dataanalysisnanodegree

Udacity data analysis nanodegree

datavisualisation

dend-data_pipeline_airflow

Learn to build a data pipeline with Airflow to automate wrangling data - An Udacity Data Engineer Nano Degree Project

dm_apache_cassandra

finding_donors

This project is designed to get you acquainted with the many supervised learning algorithms available in sklearn, and to also provide for a method of evaluating just how each model works and performs on a certain type of data. It is important in machine learning to understand exactly when and where a certain algorithm should be used, and when one should be avoided. Things you will learn by completing this project: How to identify when preprocessing is needed, and how to apply it. How to establish a benchmark for a solution to the problem. What each of several supervised learning algorithms accomplishes given a specific dataset. How to investigate whether a candidate solution model is adequate for the problem.

identify_customer_segments

In this project, you will work with real-life data provided to us by our Bertelsmann partners AZ Direct and Arvato Finance Solution. The data here concerns a company that performs mail-order sales in Germany. Their main question of interest is to identify facets of the population that are most likely to be purchasers of their products for a mailout campaign. Your job as a data scientist will be to use unsupervised learning techniques to organize the general population into clusters, then use those clusters to see which of them comprise the main user base for the company. Prior to applying the machine learning methods, you will also need to assess and clean the data in order to convert the data into a usable form.

jing_s_data_collectior

This is a data collector for my friend Jingjing, a young lady study in Trinity College Dublin. It helps her to generate specific CSV file from world bank API and other resources.

pdsnd_github

GitHub project (Project 3) repository for PDSND

pythonfords

Full mark coursework of Python for Data Science

sakila_movie_db_investigation

The Sakila movie database is a SQL database of online DVD rentals, this repository will queue the database to answer questions about business decision.

udacity-dataeng-project1

Udacity Data Engineering Nanodegree Project 1 - Data Modeling with Postgres

wrangle-and-analyze-data