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I learned about the implementation of a Decision Tree Classifier in python using scikit-learn. I've calculated the Entropy, Gini Impurity and the Information Gain. I've done all this with 100% practice.

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https://www.kaggle.com/muhammadrameez242 , ye meri kaggle ki I'd hai yha par Ap mukamal assignments simple roman urdu mein mill jai gi codes mein

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https://dreampuf.github.io/GraphvizOnline/ . this is the online previewer for dot files

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I have done this video with 100% practice.

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I have done this lecture with 100% practice.

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The main point is that when we remove the alive column the model performs well and graph representation becomes better.

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I also learned in this lecture how to code a decision tree algorithm for classification in PythonSteps of DECISION TREE in Python1-Import libraries
2-Load the data set of TITANIC
3-Drop the deck column
4-Impute missing values of age, and fare using median
5-Impute missing values of embark and embarked_town using the mode
6- Encode the categorical and object variables using for loop and label encoder
7-Split the data into X and y
8-Split the data into train and tests.
9-Create and train the model with prediction
10-Predict the model
11-Evaluate the model
12-Save the decision tree classifierALLAH PAK aap ko sahat o aafiat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey,Ameen.

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