- Sort Score
- Num 10 results
- Language All
- Labels All
Results 1 - 10 of 195 for pipe (0.61 seconds)
Filter
-
Announcing Elastic’s piped query language, ES|Q...
From pipe dreams to reality: Announcing Elastic’s piped query...technical preview of Elastic®’s new piped query language, ES|QL (Elasticsearch...www.elastic.co/blog/esql-elasticsearch-piped-query-language -
Elasticsearch Piped Query Language (ES|QL) | El...
investigation: Elasticsearch Piped Query Language (ES|QL) Try our...next-generation transformative piped query language and engine —...www.elastic.co/elasticsearch/piped-query-language -
Elastic Security 8.11 adds piped queries, enhan...
11: Piped queries, AI assistance, and...Elastic Security 8.11 introduces pipe queries with Elasticsearch Query...www.elastic.co/blog/whats-new-elastic-security-8-11-0 -
7.1. Pipelines and composite estimators — sciki...
SVC ())] >>> pipe = Pipeline ( estimators ) >>> pipe Pipeline(s...pipeline: >>> pipe . steps [ 0 ] ('reduce_dim', PCA()) >>> pipe [ 0 ]...scikit-learn.org/stable/modules/compose.html -
Pipelining: chaining a PCA and a logistic regre...
1 ) pipe = Pipeline ( steps = [( "scaler"...), } search = GridSearchCV ( pipe , param_grid , n_jobs = 2 )...scikit-learn.org/stable/auto_examples/compose/plot_digits_pipe.html -
Release Highlights for scikit-learn 1.0 — sciki...
LogisticRegression ()) pipe . fit ( X , y ) pipe [: - 1 ] . get_feature_names_out...the latest version (with pip): pip install -- upgrade scikit...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html -
Recursive feature elimination — scikit-learn 1....
] ) pipe . fit ( X , y ) ranking = pipe . named_steps...), - 1 )) y = digits . target pipe = Pipeline ( [ ( "scaler" ,...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html -
Supervised fine-tuning of the open source IBM G...
the text generation pipeline pipe = pipeline( task= "text-generation"...{question} [/INST]" generated = pipe(prompt) predicted_answer = generated[...developer.ibm.com/articles/awb-supervised-finetuning-ibm-granite-model-transformers/ -
Getting Started — scikit-learn 1.8.0 documentation
create a pipeline object >>> pipe = make_pipeline ( ... StandardScaler...# fit the whole pipeline >>> pipe . fit ( X_train , y_train )...scikit-learn.org/stable/getting_started.html -
TfidfTransformer — scikit-learn 1.8.0 documenta...
'one' ] >>> pipe = Pipeline ([( 'count' , CountVectorizer...TfidfTransformer ())]) . fit ( corpus ) >>> pipe [ 'count' ] . transform ( corpus...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html