Day-19

Day 19 of #100DaysOfCode

Task

1. Intro to Machine Learning Course
2. Intermediate Machine Learning Course (not done)

Resources

• Kaggle's Intro to Machine Learning course

• • Lesson 1: How Models Work
• • Lesson 2: Basic Data Exploration - My Notebok
• • Lesson 3: Your First Machine Learning Model - My Notebok
• • Lesson 4: Model Validation - My Notebok
• • Lesson 5: Underfitting and Overfitting - My Notebok
• • Lesson 6: Random Forests - My Notebok
• • Lesson 7: Machine Learning Competition - My Notebok

• Kaggle House price prediction Challenge

• • My Notebook

Topics I have learnt

1. Intro to Machine Learning Course

• How Models Work
• Exploring data
• Decision Trees (DecisionTreeRegressor)
• Random Forest (RandomForestRegressor)
• Overfitting and Underfitting data
• Model Validation using MAE (mean absolute error)

2. Also did house price prediction

Software used

• Jupyter Notebook
• Python 3.10.2
• Numpy 1.22.4
• pandas 1.4.2
• scikit-learn 1.1.1

My Notebooks

• L2 - Explore_your_data.ipynb
• L3 - Your_first_machine_learning_model.ipynb
• L4 - Model_validation.ipynb
• L5 - Underfitting_and_Overfitting.ipynb
• L6 - Random_forests.ipynb
• L7 - Machine_learning_competitions.ipynb
• House_price_prediction_v1.ipynb

Conclusion:

Today I learned how models work - DecisionTreeRegressor, RandomForestRegressor, overfitting & underfitting data and model validation using MAE. Also did house price prediction. Actually I have done both Intro to ML and Intermediate ML course a year ago, but I forgot almost everything, so doing it again, now doing it seriously. Not did Intermediate ML course today, rather did some house price prediction on things which I have learnt.