<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">🔢 (⚖️ 🔢) 💪 🐍</a> ↩️ ⏬ 3️⃣.4️⃣.

///

/// tip

🚥 👆 💭, "📊", "🎓", &amp; "🍏" 📛 🎰 🏫 <abbr title="Technically, Deep Learning model architectures">🏷</abbr>.

///

### 📣 *➡ 🔢*

⤴️ ✍ *➡ 🔢* ⏮️ 🆎 ✍ ⚙️ 🔢 🎓 👆 ✍ (`ModelName`):

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### ✅ 🩺

link: https://eng.uber.com/ludwig-v0-2/ title: 'Uber: Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox [including a FastAPI server]' - author: Maarten Grootendorst author_link: https://www.linkedin.com/in/mgrootendorst/ link: https://towardsdatascience.com/how-to-deploy-a-machine-learning-model-dc51200fe8cf title: How to Deploy a Machine Learning Model - author: Johannes Gontrum author_link: https://x.com/gntrm link: https://medium.com/@gntrm/jwt-authentication-w...

... 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.

cat > testobject << EOF
MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.
EOF
```

Upload this object to the bucket via `mc cp`
```
mc cp testobject myminio/functionbucket/
```

## Invoke Lambda transformation via PresignedGET

///

/// tip | Dica



///

	Se você está se perguntando, "AlexNet", "ResNet", e "LeNet" são apenas nomes de <abbr title="técnicamente, modelos de arquitetura de Deep Learning">modelos</abbr> de Machine Learning (aprendizado de máquina).

### Declare um *parâmetro de rota*

Logo, crie um *parâmetro de rota* com anotações de tipo usando a classe enum que você criou (`ModelName`):

///

/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

### Deklarieren Sie einen *Pfad-Parameter*

You can declare extra information in `Field`, `Query`, `Body`, etc. And it will be included in the generated JSON Schema.

You will learn more about adding extra information later in the docs, when learning to declare examples.

/// warning

Extra keys passed to `Field` will also be present in the resulting OpenAPI schema for your application.

import org.codelibs.fess.util.ComponentUtil;
import org.opensearch.search.rescore.QueryRescorerBuilder;
import org.opensearch.search.rescore.RescorerBuilder;

/**
 * Learning to Rank query rescorer implementation.
 */
public class LtrQueryRescorer implements QueryRescorer {

    /**
     * Default constructor.
     */
    public LtrQueryRescorer() {
        // Default constructor

///

/// tip | Порада

Якщо вам цікаво, "AlexNet", "ResNet" та "LeNet" — це просто назви ML моделей <abbr title="Технічно, архітектури Deep Learning моделей">Machine Learning</abbr>.

///


### Оголосіть *параметр шляху*

Потім створіть *параметр шляху* з анотацією типу, використовуючи створений вами клас enum (`ModelName`):

unprofessional or unwelcome in the community.

**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.

### 2. Warning

**Community Impact**: A violation through a single incident or series
of actions.

**Consequence**: A warning with consequences for continued behavior. No