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Introducing Elasticsearch Relevance Engine (ESR...
models (LLMs). Even better, it’s accessible via a simple, unified...solely on a model’s so-called "parametric" knowledge. Supercharged...www.elastic.co/search-labs/blog/introducing-elasticsearch-relevance-engine-esre -
LLM observability | Track AI safety, costs, and...
multi-modal models, including text, video, and images, enabling...OpenTelemetry. This can be supported with EDOT (Java, Python, Node.js)...www.elastic.co/observability/llm-monitoring -
A look into the future for observability: 2023 ...
observability. Teams will require out-of-the-box, domain-specific...data, becomes increasingly important. Full-stack, cloud-native...www.elastic.co/blog/observability-predictions-trends-2023 -
Log analytics | Elastic
services, CI/CD pipelines, databases, Kubernetes, and more. Automatic...Filter, transform, join, correlate, and aggregate logs. ES|QL...www.elastic.co/observability/log-monitoring -
WhiteKernel — scikit-learn 1.7.2 documentation
True ) (array([653.0, 592.1 ]), array([316.6, 316.6])) __call__...noise_level_bounds = (1e-05, 100000.0) ) [source] # White kernel. The main...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.WhiteKernel.html -
Ridge — scikit-learn 1.7.2 documentation
solver {‘auto’, ‘svd’, ‘cholesky’, ‘lsqr’, ‘sparse_cg’, ‘sag’, ‘saga’,...sparse data. However, only ‘lsqr’, ‘sag’, ‘sparse_cg’, and ‘lbfgs’...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html -
class_likelihood_ratios — scikit-learn 1.7.2 do...
class_likelihood_ratios ([ 0 , 1 , 0 , 1 , 0 ], [ 1 , 1 , 0 , 0 , 0 ]) (1.5,...{"LR+": 1.0, "LR-": 1.0} a dict in the format {"LR+": value_1, "LR-":...scikit-learn.org/stable/modules/generated/sklearn.metrics.class_likelihood_ratios.html -
Lasso — scikit-learn 1.7.2 documentation
linear_model . Lasso ( alpha = 0.1 ) >>> clf . fit ([[ 0 , 0 ], [ 1 , 1...is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html -
KNNImputer — scikit-learn 1.7.2 documentation
array([[1. , 2. , 4. ], [3. , 4. , 3. ], [5.5, 6. , 5. ], [8. , 8....], [ 3 , 4 , 3 ], [ np . nan , 6 , 5 ], [ 8 , 8 , 7 ]] >>> imputer...scikit-learn.org/stable/modules/generated/sklearn.impute.KNNImputer.html -
SpectralEmbedding — scikit-learn 1.7.2 document...
affinity {‘nearest_neighbors’, ‘rbf’, ‘precomputed’, ‘precomput...{‘arpack’, ‘lobpcg’, ‘amg’}, default=None The eigenvalue decomposition...scikit-learn.org/stable/modules/generated/sklearn.manifold.SpectralEmbedding.html