Back for good
Happy to learn math again.
This month, I learn to do a full-stack data engineer with a goal in mind that is to develop and deploy a data science project. I break it down into smaller steps:
- Build a web app to display some charts based on demo data. I use the Streamlit framework to do it.
- streamlit run app.py
- Apply to the company’s database: read an exported CSV file, clean data, and build basic charts. (My teammate gave me the CSV file)
- Setup Docker to be a localhost server to connect with the Postgres database managed by pgAdmin app. Write SQL queries to explore the database. (My team helped me to setup Docker and database for localhost)
- Install Docker, have a file docker-compose.yml
- Terminal: docker -compose up
- Open properties of the database (PyCharm) to fix user/password (if nee)
- Open pgAdmin to restart server.
- Connect to the cloud database.
- Deploy source code to the Azure server.
So this month ends with a go-live project that I have learned a lot along the way. The great thing is now I can apply the data science knowledge that I studied before to the real project for the company. Next month I will start to study Deep Learning, which is the higher-level — intermediate, compared to Machine Learning — beginner. Excited to think about it. I am pretty sure that the feeling of doing Data Science, ML/DL will be as interesting as the feeling of doing maths that I enjoyed so much back then.
Once again, it’s cool to look at the little thing that was done :)
Houze HQ, 29 May 2020.