## Full Stack FastAPI MongoDB

... 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.

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

Production'da nasıl oldugunu görmek için şu bölüme bakın [Deployment](deployment/index.md){.internal-link target=_blank}.

## `async` ve `await`

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/
```

        "//tensorflow/core:framework",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/grappler:grappler_item",
        "//tensorflow/core/grappler/clusters:single_machine",
        "//tensorflow/core/grappler/costs:graph_properties",
        "//tensorflow/core/grappler/inputs:trivial_test_graph_input_yielder",
        "//tensorflow/core/protobuf:error_codes_proto_impl_cc",
    ],

* **Intuitif** : Excellente compatibilité avec les IDE. <abbr title="également connu sous le nom d'auto-complétion, autocomplétion, IntelliSense">Complétion</abbr> complète. Moins de temps passé à déboguer.
* **Facile** : Conçu pour être facile à utiliser et à apprendre. Moins de temps passé à lire la documentation.
* **Concis** : Diminue la duplication de code. De nombreuses fonctionnalités liées à la déclaration de chaque paramètre. Moins de bugs.

## 1. Prerequisites

* Familiarity with [Docker Compose](https://docs.docker.com/compose/overview/).
* Docker installed on your machine. Download the relevant installer from [here](https://www.docker.com/community-edition#/download).

## 2. Run Distributed MinIO on Docker Compose

## Görüşler

"_[...] Bugünlerde **FastAPI**'ı çok fazla kullanıyorum. [...] Aslında bunu ekibimin **Microsoft'taki Machine Learning servislerinin** tamamında kullanmayı planlıyorum. Bunlardan bazıları **Windows**'un ana ürünlerine ve **Office** ürünlerine entegre ediliyor._"

MinIO uses [`klauspost/compress/s2`](https://github.com/klauspost/compress/tree/master/s2)
streaming compression due to its stability and performance.

This algorithm is specifically optimized for machine generated content.
Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

## 服务器主机和服务器程序

关于名称，有一个小细节需要记住。 💡

“**服务器**”一词通常用于指远程/云计算机（物理机或虚拟机）以及在该计算机上运行的程序（例如 Uvicorn）。

请记住，当您一般读到“服务器”这个名词时，它可能指的是这两者之一。

当提到远程主机时，通常将其称为**服务器**，但也称为**机器**(machine)、**VM**（虚拟机）、**节点**。 这些都是指某种类型的远程计算机，通常运行 Linux，您可以在其中运行程序。


## 安装服务器程序

您可以使用以下命令安装 ASGI 兼容服务器：

=== "Uvicorn"