Back

Back

Back

[Project 01]

Achieved accuarte job-skill matches on a small dataset from TNIC.

Machine Learning

Job-Skill Matching Using Machine Learning

[Project Overview]

An accurate, ML-based tool that connects candidate skills with the right job roles, making hiring smarter and faster.

[Details]

As part of my Business Data Mining course (DSA-301) and Discrete Mathematics course (DSA-102) at Thai-Nichi International College, I collaborated with two teammates on this interdisciplinary project focused on matching individuals to jobs on their skill sets using machine learning.


We experimented with multiple classification algorithms to evaluate their performance on a small-scale categorical dataset. After the comparative testing, the K-Nearest Neighbors (KNN) Model was selected as our final approach, as it delivered the highest accuracy for the given data.

[Industry]

Machine Learning

[My Role]

Analytics & Research Lead

[Platforms]

Google Colab || Google Site

[Timeline]

Aug 2024 - Oct 2024

View Google Site

View Google Site

View Google Site

[My Contributions]
[01] Data Collection & Preparation

Collected the dataset through Google Forms

Handled data cleaning and transformation

Also contributed to preprocessing tasks

[01] Data Collection & Preparation

Collected the dataset through Google Forms

Handled data cleaning and transformation

Also contributed to preprocessing tasks

[01] Data Collection & Preparation

Collected the dataset through Google Forms

Handled data cleaning and transformation

Also contributed to preprocessing tasks

[02] Exploratory Data Analysis (EDA)

Visualized job distribution and skill frequencies using bar charts and radar charts

Analyzed soft skills across job types

Created a correlation matrix and heat map to explore skill interrelationships

[02] Exploratory Data Analysis (EDA)

Visualized job distribution and skill frequencies using bar charts and radar charts

Analyzed soft skills across job types

Created a correlation matrix and heat map to explore skill interrelationships

[02] Exploratory Data Analysis (EDA)

Visualized job distribution and skill frequencies using bar charts and radar charts

Analyzed soft skills across job types

Created a correlation matrix and heat map to explore skill interrelationships

[03] Presentations & Communication

Took primary responsibility for three out of four major presentations during the course of the project

Content creation and delivery

Played an active role in the final project defense, presenting key findings and model outcomes

[03] Presentations & Communication

Took primary responsibility for three out of four major presentations during the course of the project

Content creation and delivery

Played an active role in the final project defense, presenting key findings and model outcomes

[03] Presentations & Communication

Took primary responsibility for three out of four major presentations during the course of the project

Content creation and delivery

Played an active role in the final project defense, presenting key findings and model outcomes

[04] Project Documentation & Web Design

Contributed significantly to the development and design of our Google Site, where we showcased our methodology, findings, and visual insights

[04] Project Documentation & Web Design

Contributed significantly to the development and design of our Google Site, where we showcased our methodology, findings, and visual insights

[04] Project Documentation & Web Design

Contributed significantly to the development and design of our Google Site, where we showcased our methodology, findings, and visual insights

[Key Learnings]
Machine Learning Application

Applied K-Nearest Neighbors (KNN) to real-world categorical data.

Machine Learning Application

Applied K-Nearest Neighbors (KNN) to real-world categorical data.

Machine Learning Application

Applied K-Nearest Neighbors (KNN) to real-world categorical data.

Data Handling and EDA

Enhanced data quality through cleaning, visualization, and feature analysis.

Data Handling and EDA

Enhanced data quality through cleaning, visualization, and feature analysis.

Data Handling and EDA

Enhanced data quality through cleaning, visualization, and feature analysis.

Technical Communication

Improved abiility to document and present data-driven insights.

Technical Communication

Improved abiility to document and present data-driven insights.

Technical Communication

Improved abiility to document and present data-driven insights.

Select this text to see the highlight effect

Create a free website with Framer, the website builder loved by startups, designers and agencies.