Study Session - Anki - Scikit Learn, Model Selection, RandomForestClassifier, Cross Val Score 5.7.21

This is just a study session of me reviewing my flashcards and going over the code in Google Colab.

This video is for beginners transitioning into intermediate level with Scikit-Learn / want to learn more about functions used with scikit-learn.

In this video, I go over my custom flashcards created with Anki. Anki is useful because it focuses on Spaced Repetition.

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☑️ Github for code for Code in Video:

X_train, X_test, y_train,y_test = train_test_split(X,y,test_size=0.2)
import numpy as np
rf_params = {'n_estimator' : [100,200,400,500],
'max_depth': [2,1,0,5],
'max_features': ['auto','sqrt'],
'min_samples_split': range(2, 403, 10),
'min_samples_leaf': [1,2,3,4]
}

rf_rscv = RandomizedSearchCV(clf, param_distributions=rf_params, n_iter=10, cv=5, verbose=2)

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