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ChatGPT and Elasticsearch: OpenAI meets private...
proprietary software or internal documentation. Users should, therefore,...ChatGPT access to specific documents relevant to your domain and...www.elastic.co/search-labs/blog/chatgpt-elasticsearch-openai-meets-private-data -
Topic extraction with Non-negative Matrix Facto...
only one document or in at least 95% of the documents are removed....text documents using k-means Clustering text documents using...scikit-learn.org/stable/auto_examples/applications/plot_topics_extraction_with_nmf_lda.html -
1.13. Feature selection — scikit-learn 1.7.1 do...
The classes in the sklearn.feature_selection module can be used for feature selection/dimensionality reduction on sample sets, either to improve estimators’ accuracy scores or to boost their perfor...scikit-learn.org/stable/modules/feature_selection.html -
A demo of the mean-shift clustering algorithm —...
Reference: Dorin Comaniciu and Peter Meer, “Mean Shift: A robust approach toward feature space analysis”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2002. pp. 603-619. Generate...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
7.3. Preprocessing data — scikit-learn 1.7.1 do...
The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that is more suitable for the downstream esti...scikit-learn.org/stable/modules/preprocessing.html -
Ledoit-Wolf vs OAS estimation — scikit-learn 1....
The usual covariance maximum likelihood estimate can be regularized using shrinkage. Ledoit and Wolf proposed a close formula to compute the asymptotically optimal shrinkage parameter (minimizing a...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
L1-based models for Sparse Signals — scikit-lea...
The present example compares three l1-based regression models on a synthetic signal obtained from sparse and correlated features that are further corrupted with additive gaussian noise: a Lasso;, a...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
9. Computing with scikit-learn — scikit-learn 1...
Strategies to scale computationally: bigger data- Scaling with instances using out-of-core learning., Computational Performance- Prediction Latency, Prediction Throughput, Tips and Tricks., Paralle...scikit-learn.org/stable/computing.html -
Model-based and sequential feature selection — ...
This example illustrates and compares two approaches for feature selection: SelectFromModel which is based on feature importance, and SequentialFeatureSelector which relies on a greedy approach. We...scikit-learn.org/stable/auto_examples/feature_selection/plot_select_from_model_diabetes.html -
2.8. Density Estimation — scikit-learn 1.7.1 do...
Density estimation walks the line between unsupervised learning, feature engineering, and data modeling. Some of the most popular and useful density estimation techniques are mixture models such as...scikit-learn.org/stable/modules/density.html