Machine Learning Course on BTK Akademi

This repository contains exercises and materials from the BTK Akademi Machine Learning Course. In addition I have complete 2 project: Classification Project: Airline Passenger Satisfaction and Regression Project: Urban Air Quality and Health Impact Analysis. I obtained dataset from Kaggle. Below, you will find details about the courses, as well as links to the course materials and certifications.

Classification Project : Airline Passenger Satisfaction

Overview

This project focuses on classifying categorical data using a Support Vector Classifier (SVC).

Model Evaluation

Support Vector Machine (SVM)

		  precision    recall  f1-score   support

       0       0.93      0.95      0.94     14573
       1       0.94      0.91      0.92     11403

accuracy                           0.93     25976
macro avg      0.93      0.93      0.93     25976
weighted avg   0.93      0.93      0.93     25976

Conclusion

The model achieved strong performance with a 90% accuracy. Further enhancements may include hyperparameter tuning or experimenting with alternative classification algorithms.

Regression Project : Urban Air Quality and Health Impact Analysis

Overview

This project involves predicting continuous target variables using Lineer Regression, Polinomial Regressior, Decision Tree Regressor, KNN Regressor, Random Forest Regressior models.

Model Evaluation

Model	MSE	R2 Score
Lineer Regression (col=Severity_Score)	0.271174	0.37570
Polinomial Regressior(all 9 columns)	0.029113	0.93297
Decision Tree Regressior	0.02529	0.94177
KNN Regressor	0.00629	0.98550
Random Forest Regressior	0.01683	0.96123

Courses

Machine Learning Course (11+ hours)

This course provides a comprehensive introduction to machine learning concepts and techniques.

Machine Learning Hands-on with Python (8+ hours)

This course focuses on practical applications of machine learning using Python, offering hands-on experience with real-world projects.

Certifications