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  1. Grandma Shows Off Her First Cell Phone And The ...

    fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...
    digg.com/digg-vids/link/first-cellphone-ever-made-grandma-funny-video
    Sat Nov 23 01:22:18 UTC 2024
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  2. check_X_y — scikit-learn 1.5.2 documentation

    accept_sparse = False , * , accept_large_sparse = True , dtype = 'numeric'...'numeric' , order = None , copy = False , force_writeable = False , force_all_finite...
    scikit-learn.org/stable/modules/generated/sklearn.utils.check_X_y.html
    Thu Nov 21 22:17:10 UTC 2024
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  3. Image denoising using kernel PCA — scikit-learn...

    random_state = 0 , train_size = 1_000 , test_size = 100 ) rng = np ....axs = plt . subplots ( nrows = 10 , ncols = 10 , figsize = ( 8...
    scikit-learn.org/stable/auto_examples/applications/plot_digits_denoising.html
    Sat Nov 23 04:49:14 UTC 2024
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  4. Train error vs Test error — scikit-learn 1.5.2 ...

    n_informative = 50 , shuffle = False , noise = 1.0 , coef = True , )...l1_ratio = 0.7 , max_iter = 10000 ) train_errors = list () test_errors...
    scikit-learn.org/stable/auto_examples/model_selection/plot_train_error_vs_test_error.html
    Fri Nov 22 23:53:26 UTC 2024
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  5. Visualization of MLP weights on MNIST — scikit-...

    max_iter = 8 , alpha = 1e-4 , solver = "sgd" , verbose = 10 , random_state...return_X_y = True , as_frame = False ) X = X / 255.0 # Split data...
    scikit-learn.org/stable/auto_examples/neural_networks/plot_mnist_filters.html
    Fri Nov 22 23:53:26 UTC 2024
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  6. Gaussian Mixture Model Selection — scikit-learn...

    ( X [ Y_ == i , 0 ], X [ Y_ == i , 1 ], 0.8 , color = color )...data = df , kind = "bar" , x = "Number of components" , y = "BIC...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_selection.html
    Sat Nov 23 04:49:16 UTC 2024
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  7. locally_linear_embedding — scikit-learn 1.5.2 d...

    reg = 0.001 , eigen_solver = 'auto' , tol = 1e-06 , max_iter...max_iter = 100 , method = 'standard' , hessian_tol = 0.0001 , modified_tol...
    scikit-learn.org/stable/modules/generated/sklearn.manifold.locally_linear_embedding.html
    Thu Nov 21 22:17:08 UTC 2024
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  8. partial_dependence — scikit-learn 1.5.2 documen...

    sample_weight = None , categorical_features = None , feature_names = None...grid_resolution = 100 , method = 'auto' , kind = 'average' ) [source]...
    scikit-learn.org/stable/modules/generated/sklearn.inspection.partial_dependence.html
    Fri Nov 22 23:53:26 UTC 2024
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  9. 1.11. Ensembles: Gradient boosting, random fore...

    min_samples_leaf = 1 , ... max_depth = 2 , ... learning_rate = 1 , ......learning_rate = 1.0 , ... max_depth = 1 , random_state = 0 ) . fit...
    scikit-learn.org/stable/modules/ensemble.html
    Sat Nov 23 04:49:16 UTC 2024
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  10. safe_sparse_dot — scikit-learn 1.5.2 documentation

    dense_output = False ) [source] # Dot product...matrix} dense_output bool, default=False When False, a and b both...
    scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.safe_sparse_dot.html
    Thu Nov 21 22:17:08 UTC 2024
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