Decision tree algorithm is used to solve classification problem in machine learning domain. In this tutorial we will solve employee salary prediction problem using decision tree. First we will go over some theory and then do coding practice. In the end I’ve a very interesting exercise for you to solve.

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Code: https://github.com/codebasics/py/blob/master/ML/9_decision_tree/9_decision_tree.ipynb

csv file for exercise: https://github.com/codebasics/py/blob/master/ML/9_decision_tree/Exercise/titanic.csv

Exercise solution: https://github.com/codebasics/py/blob/master/ML/9_decision_tree/Exercise/9_decision_tree_exercise.ipynb

Topics that are covered in this Video:
0:00 – How to solve classification problem using decision tree algorithm?
0:26 – Theory (Explain rationale behind decision tree using a use case of predicting salary based on department, degree and company that a person is working for)
2:10 – How do you select ordering of features? High vs low information gain and entropy
3:52 – Gini impurity
4:28 – Coding (start)
9:11 – Create sklearn model using DecisionTreeClassifier
13:32 – Exercise (Find out survival rate of titanic ship passengers using decision tree)

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Machine Learning Tutorial Python – 10 Support Vector Machine (SVM): https://www.youtube.com/watch?v=FB5EdxAGxQg&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw&index=11

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