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Python Question / Quiz;
What is the output of the following Python code, and why? π€π Comment your answers below! π
What is the output of the following Python code, and why? π€π Comment your answers below! π
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Python Question / Quiz;
What is the output of the following Python code, and why? π€π Comment your answers below! π
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Python Question / Quiz;
What is the output of the following Python code, and why? π€π Comment your answers below! π
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Forwarded from Python | Machine Learning | Coding | R
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What is a common use case for the PCA (Principal Component Analysis) algorithm in machine learning?
A) Hyperparameter tuning
B) Data visualization and dimensionality reduction
C) Gradient descent optimization
D) Model ensembling
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What is a common use case for the PCA (Principal Component Analysis) algorithm in machine learning?
A) Hyperparameter tuning
B) Data visualization and dimensionality reduction
C) Gradient descent optimization
D) Model ensembling
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Question 2 (Advanced):
In machine learning with Python, what does the
A) Controls the shuffling applied to the data before splitting
B) Sets the percentage of data to use for testing
C) Determines the number of CPU cores to use
D) Specifies the type of ML algorithm to apply
#Python #MachineLearning #ScikitLearn #DataScience
In machine learning with Python, what does the
random_state
parameter do in scikit-learn's train_test_split()
function?A) Controls the shuffling applied to the data before splitting
B) Sets the percentage of data to use for testing
C) Determines the number of CPU cores to use
D) Specifies the type of ML algorithm to apply
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Question 4 (Intermediate):
In scikit-learn's KMeans implementation, what is the purpose of the
A) Number of initial centroid configurations to try
B) Number of iterations for each run
C) Number of features to initialize
D) Number of CPU cores to use
#Python #KMeans #Clustering #MachineLearning
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In scikit-learn's KMeans implementation, what is the purpose of the
n_init
parameter? A) Number of initial centroid configurations to try
B) Number of iterations for each run
C) Number of features to initialize
D) Number of CPU cores to use
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