Use the link below to view the Jupyter Notebook. If you have problem loading the entire notebook in the first link, please use the second one.
This is a practice for data science analysis. This is not yet finished but already has all the sections a project should have. I will be updating the jupyter notebook constantly.
The targats for this practice:
- Take this excercise as a preparation for kaggle competitions
- Hands-on experience to data analysis, cleaning and modeling
- Review visual analytic skills (matplotlib and seaborn)
- Use interactive ploting module: plotly (taking a Udemy course now)
- Define the problem and understand the data
- Data Cleaning
- Feature Engineering
- Exploratory Data Analysis
- Single Variable Analysis
- Multiple Variable Analysis
- Correlation Analysis
- Model Selection
- Model Improvement