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sg_gallery-rendered-html.css
var(--sg-text-color); background-color: var(--sg-text-color);...html[data-theme="light"] { --sg-text-color: #000; --sg-background-color:...scikit-learn.org/stable/_static/sg_gallery-rendered-html.css -
PropertyResolver (Spring Framework 7.0.1 API)
text) Resolve ${...} placeholders in the given text, replacing... text) Resolve ${...} placeholders in the given text, replacing...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/core/env/PropertyRes... -
JSON prompting for LLMs - IBM Developer
such as text, code, metrics, or text-based image descriptions,...structure. When you communicate in text format, ambiguity can creep...developer.ibm.com/articles/json-prompting-llms/ -
Parser (Spring Framework 7.0.1 API)
String text, Locale locale) Parse a text String to produce...Parse a text String to produce a T. Parameters: text - the text...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/format/Parser.html -
What are Word Embeddings? | A Comprehensive Wor...
piece of text, such as positive, negative, or neutral. Text similarity:...predicting the next word in a sequence of text. By representing...www.elastic.co/what-is/word-embedding -
Understanding large language models: A comprehe...
text translation, classification,...and then fine-tuned to solve text classification, question answering,...www.elastic.co/what-is/large-language-models -
What is vector search? Better search with ML | ...
including text and images, transforming it...the unstructured data beyond text, such as videos, images, and...www.elastic.co/what-is/vector-search -
api-search.css
option { color: var(--pst-color-text-base); background-color: va...er { color: var(--pst-color-text-base); line-height: 0.7rem !important;...scikit-learn.org/stable/_static/styles/api-search.css -
World's most downloaded vector database: E...
vectors: Fast and efficient Sparse text expansion and dense meaning...LLMs or built-in models for text embeddings, classification,...www.elastic.co/elasticsearch/vector-database -
f1_score — scikit-learn 1.7.2 documentation
\[\text{F1} = \frac{2 * \text{TP}}{2 * \text{TP} + \text{FP}...\text{FP} + \text{FN}}\] Where \(\text{TP}\) is the number of true positives,...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html