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1-exercise-introduction.ipynb

1-exercise-introduction.ipynb

 
 

2-exercise-missing-values.ipynb

2-exercise-missing-values.ipynb

 
 

3_exercise-categorical-variables.ipynb

3_exercise-categorical-variables.ipynb

 
 

4_exercise-pipelines.ipynb

4_exercise-pipelines.ipynb

 
 

5_exercise-cross-validation.ipynb

5_exercise-cross-validation.ipynb

 
 

6_exercise-xgboost.ipynb

6_exercise-xgboost.ipynb

 
 

README.md

README.md

 
 

exercise-5-random-forests.ipynb

exercise-5-random-forests.ipynb

 
 

exercise-6-machine-learning-competitions.ipynb

exercise-6-machine-learning-competitions.ipynb

 
 

exercise_1-explore-your-data.ipynb

exercise_1-explore-your-data.ipynb

 
 

exercise_2-your-first-machine-learning-model.ipynb

exercise_2-your-first-machine-learning-model.ipynb

 
 

exercise_3-model-validation.ipynb

exercise_3-model-validation.ipynb

 
 

exercise_4-underfitting-and-overfitting.ipynb

exercise_4-underfitting-and-overfitting.ipynb

 
 

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Machine-Learning-Intro-Intermediate

This repository contains pre-requisite notebooks of Machine Learning Course from Kaggle for my internship as a Machine Learning Application Developer at Technocolabs.

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This repository contains pre-requisite notebooks of Machine Learning Course from Kaggle for my internship as a Machine Learning Application Developer at Technocolabs.

Topics

machine-learning random-forest cross-validation pipelines xgboost missing data-leakage underfitting-overfitting

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