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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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