- These are useful projects for beginners and intermediates to approaching Machine Learning. Each ipynb file is a different topic (lesson).
- Dependency: Python and some other libraries are listed in each document (ipynb files).
- Exploratory Data Analysis and create Report (Analytic_Report).
- Predict house prices using Linear Regression (Melbourne_Housing_Market).
- Clean data, visualize and analyze flight data (Airline_Arrivals_Analysis).
- Applying classification algorithms and PCA to flight data (Airline_Arrivals_Model):
- Naive Bayes
- Logistic Regression
- Decision Tree
- Random Forest
- Gradient Boosting
- Support Vector Machine
- Tran Dang Trung Duc