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Transforming Industries and the Critical Role o...
today's tech-centric world, Large Language Models (LLMs) are transforming...assistants, content creation, and speech-to-text systems. With growing...www.elastic.co/observability-labs/blog/transforming-industries-and-the-critical-role-of-llm-obser... -
Traces in Discover for Deeper Application Insig...
traces - * | WHERE span . name = = "oteldemo.CheckoutService/PlaceOrder"...traces - * | WHERE service . name = = "currency" and span . name...www.elastic.co/observability-labs/blog/elastic-discover-traces-apm -
MLPClassifier — scikit-learn 1.7.2 documentation
function, returns f(x) = 1 / (1 + exp(-x)). ‘tanh’, the hyperbolic tan...function, returns f(x) = max(0, x) solver {‘lbfgs’, ‘sgd’, ‘adam’},...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html -
RocCurveDisplay — scikit-learn 1.7.2 documentation
0.1 , 0.4 , 0.35 , 0.8 ]) >>> fpr , tpr , thresholds = metrics...np . array ([ 0 , 0 , 1 , 1 ]) >>> y_score = np . array ([ 0.1...scikit-learn.org/stable/modules/generated/sklearn.metrics.RocCurveDisplay.html -
plot_multi_metric_evaluation.rst.txt
for sample, style in (("train", "--"), ("test", "-")): sample_score_mean...plt.ylabel("Score") ax = plt.gca() ax.set_xlim(0, 402) ax.set_ylim(0.73,...scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt -
extract_patches_2d — scikit-learn 1.7.2 documen...
load_sample_image ( "china.jpg" ) >>> print ( 'Image shape: {} ' . format...format ( one_image . shape )) Image shape: (427, 640, 3) >>> patches...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.extract_patches_2d.html -
BernoulliRBM — scikit-learn 1.7.2 documentation
array ([[ 0 , 0 , 0 ], [ 0 , 1 , 1 ], [ 1 , 0 , 1 ], [ 1 , 1 , 1 ]])...learning_rate = 0.1 , batch_size = 10 , n_iter = 10 , verbose = 0 , random_state...scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html -
MaxAbsScaler — scikit-learn 1.7.2 documentation
2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , - 1. ]] >>> transformer...transformer . transform ( X ) array([[ 0.5, -1. , 1. ], [ 1. , 0. , 0....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
RepeatedKFold — scikit-learn 1.7.2 documentation
np . array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...np . array ([ 0 , 0 , 1 , 1 ]) >>> rkf = RepeatedKFold ( n_splits...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html -
load_iris — scikit-learn 1.7.2 documentation
data . target [[ 10 , 25 , 50 ]] array([0, 0, 1]) >>> list ( data...data . target_names ) [np.str_('setosa'), np.str_('versicolor'),...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html