Day-25

Day 25 of #100DaysOfCode

Task

1. Feature Engineering Course
2. House price prediction

Resources

• Kaggle's Feature Engineering Course

• • Lesson 1: What is Feature Engineering
• • Lesson 2: Mutual Information - My Notebook

• Kaggle House price prediction Challenge

• • My Notebook 1

Topics I have learnt

1. Feature Engineering

• What is Feature Engineering
• How is it useful for making Models
• Mutual Information (shows every kind of relation in data with target)

2. Did house price prediction

• With XGBRegressor & Mutual Information (high MI 50 columns)

Software used

• Jupyter Notebook
• Python 3.10.2
• Numpy 1.22.4
• pandas 1.4.2
• Matplotlib 3.5.2
• Seaborn 0.11.2
• scikit-learn 1.1.1
• XGBoost 1.6.1

My Notebooks

• L2 - Mutual Information
• House_price_prediction_9.ipynb

Conclusion:

Today I learned What is Feature Engineering, How to make data better for ML models and Mutual Information. Also did house price prediction using Mutual Information of 50 columns having high MI.