Normally when we develop a Machine Learning model and use Streamlit to turn it into a web application, comment section is practically useful for us to get interactive discussion or feedbacks from the viewers. Unfortunately, at the time of writing this blog, it seemed like Streamlit does not offer any component to suit this purpose.
Building a resume scanning system using Python
Job seekers who are usually looking for advertising jobs sometimes overwhelmed with the jobs posted on the websites. A simple search mechanism in these web pages do not really respond a good match between their resume and the job descriptions. The job seekers would need to seriously study each job description and use the same language as the job posting if they want to be shorted for an interview.
Quick report using Pivot and Grouping sets in SQL
Consider a scenario you want to create a quick report from a table product in SQL showing total product sold over the last 12 months, in which each column represents the month, last column could be the YTD sales. There will be the horizontal sub-total for each category for example sale by products, regions etc.
SQL Recursive Queries using CTEs
Have you frequently tried recursion in SQL? In Transact-SQL, we can use store procedure or function to perform a recursive call like other programing language. Another way is to rely on the Common Table Expression (or CTEs) to allow a query to reference itself in the SELECT statement.
Analysis of Sydney top performing schools
I created this project to help one of my ex-Uni friends in choosing a suitable school in Sydney for his children. This project first scraps and collects school data from various webpages and open data sources in Sydney. Then I do various analyses regarding school ranking factors. Lastly, I created heatmaps for top performing schools and an interactive marker map which can help users to locate top schools, and check their home address with the school catchment areas online.
Customer segmentation using RFM analysis
This project demonstrates a simple approach to perform customer analysis on a historical, transactional database using the RFM based segmentation. RFM stands for Recency, Frequency, and Monetary, which is one of the common techniques in CRM to categorize customers into different groups. This project used Northwind database, Azure Data Studio and Python to create RFM metrics, scores, analysis and visualizations.
Scraping and visualizing FIFA men's ranking data
The FIFA men's world ranking is a system to rank men's national teams in association football. FIFA publishes the updated ranking each month but from 2022 it has started every two months. This project demonstrates step-by-step instruction on scraping ranking data using Selenium Python package and Power BI for data visualization.
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