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  1. .zenodo.json

    {
        "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
        "license": "Apache-2.0",
        "title": "TensorFlow",
        "upload_type": "software",
        "creators": [
            {
                "name": "TensorFlow Developers"
            }
    Created: Tue Dec 30 12:39:10 GMT 2025
    - Last Modified: Tue May 18 19:19:25 GMT 2021
    - 741 bytes
    - Click Count (0)
  2. cmd/erasure-metadata-utils.go

    func readAllFileInfo(ctx context.Context, disks []StorageAPI, origbucket string, bucket, object, versionID string, readData, healing bool) ([]FileInfo, []error) {
    	metadataArray := make([]FileInfo, len(disks))
    
    	opts := ReadOptions{
    		ReadData: readData,
    		Healing:  healing,
    	}
    
    	g := errgroup.WithNErrs(len(disks))
    	// Read `xl.meta` in parallel across disks.
    	for index := range disks {
    Created: Sun Dec 28 19:28:13 GMT 2025
    - Last Modified: Fri Aug 29 02:39:48 GMT 2025
    - 11.7K bytes
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  3. docs/es/docs/_llm-test.md

    * <abbr title="Un método de machine learning que usa redes neuronales artificiales con numerosas capas ocultas entre las capas de entrada y salida, desarrollando así una estructura interna completa">Deep Learning</abbr>
    
    ### El abbr da una frase completa y una explicación { #the-abbr-gives-a-full-phrase-and-an-explanation }
    
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Tue Dec 16 16:16:35 GMT 2025
    - 12.6K bytes
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  4. compat/maven-compat/src/main/java/org/apache/maven/project/path/DefaultPathTranslator.java

                        // Take out basedir expression and the leading slash
                        s = chopLeadingFileSeparator(s.substring(basedirExpr.length()));
                    } else {
                        s = ".";
                    }
                }
            }
    
            return s;
        }
    
        /**
         * Removes the leading directory separator from the specified filesystem path (if any). For platform-independent
    Created: Sun Dec 28 03:35:09 GMT 2025
    - Last Modified: Fri Jun 06 14:28:57 GMT 2025
    - 7.2K bytes
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  5. docs/de/docs/_llm-test.md

    * <abbr title="Eine Methode des Machine Learning, die künstliche neuronale Netze mit zahlreichen versteckten Schichten zwischen Eingabe- und Ausgabeschicht verwendet und so eine umfassende interne Struktur entwickelt">Deep Learning</abbr>
    
    ### Das abbr gibt eine vollständige Phrase und eine Erklärung { #the-abbr-gives-a-full-phrase-and-an-explanation }
    
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Wed Dec 17 07:17:04 GMT 2025
    - 12.6K bytes
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  6. internal/s3select/sql/parser.go

    }
    
    // UnaryTerm represents a single negated term or a primary term
    type UnaryTerm struct {
    	Negated *NegatedTerm `parser:"  @@"`
    	Primary *PrimaryTerm `parser:"| @@"`
    }
    
    // NegatedTerm has a leading minus sign.
    type NegatedTerm struct {
    	Term *PrimaryTerm `parser:"\"-\" @@"`
    }
    
    // PrimaryTerm represents a Value, Path expression, a Sub-expression
    // or a function call.
    type PrimaryTerm struct {
    Created: Sun Dec 28 19:28:13 GMT 2025
    - Last Modified: Thu Jan 18 07:03:17 GMT 2024
    - 12.9K bytes
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  7. docs/tr/docs/project-generation.md

    ... müsaitliğime ve diğer faktörlere bağlı olarak daha sonra gelebilir. 😅 🎉
    
    ## Machine Learning modelleri, spaCy ve FastAPI
    
    GitHub: <a href="https://github.com/microsoft/cookiecutter-spacy-fastapi" class="external-link" target="_blank">https://github.com/microsoft/cookiecutter-spacy-fastapi</a>
    
    ### Machine Learning modelleri, spaCy ve FastAPI - Features
    
    * **spaCy** NER model entegrasyonu.
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Mon Jul 29 23:35:07 GMT 2024
    - 6K bytes
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  8. docs/fr/docs/async.md

    * L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Sun Aug 31 09:56:21 GMT 2025
    - 25.4K bytes
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  9. docs/en/docs/advanced/events.md

    ## Use Case { #use-case }
    
    Let's start with an example **use case** and then see how to solve it with this.
    
    Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖
    
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Wed Dec 17 20:41:43 GMT 2025
    - 7.9K bytes
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  10. docs/pt/docs/advanced/events.md

    ## Caso de uso { #use-case }
    
    Vamos começar com um exemplo de **caso de uso** e então ver como resolvê-lo com isso.
    
    Vamos imaginar que você tem alguns **modelos de machine learning** que deseja usar para lidar com as requisições. 🤖
    
    Created: Sun Dec 28 07:19:09 GMT 2025
    - Last Modified: Wed Dec 17 20:41:43 GMT 2025
    - 8.8K bytes
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