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  1. ci/devinfra/docker_windows/Dockerfile

        [Environment]::SetEnvironmentVariable('HOME', 'C:\Users\ContainerAdministrator\', 'Machine'); \
        [Environment]::SetEnvironmentVariable('HOMEDRIVE', 'C:', 'Machine'); \
        [Environment]::SetEnvironmentVariable('HOMEPATH', '\Users\ContainerAdministrator\', 'Machine'); \
        [Environment]::SetEnvironmentVariable('GOROOT', 'C:\Program Files\Go\', 'Machine'); \
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    - Registered: Tue May 07 12:40:20 GMT 2024
    - Last Modified: Fri Aug 18 17:24:20 GMT 2023
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  2. README.md

    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.
    
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    - Registered: Sun May 05 19:28:20 GMT 2024
    - Last Modified: Wed Feb 14 17:51:34 GMT 2024
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  3. docs/en/docs/deployment/concepts.md

    ### Server Memory
    
    For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.
    
    And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨
    
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    - Registered: Sun May 05 07:19:11 GMT 2024
    - Last Modified: Thu May 02 22:37:31 GMT 2024
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  4. apache-maven/src/assembly/maven/conf/settings.xml

     |
     |                 -s /path/to/user/settings.xml
     |
     |  2. Global Level. This settings.xml file provides configuration for all Maven
     |                 users on a machine (assuming they're all using the same Maven
     |                 installation). It's normally provided in
     |                 ${maven.conf}/settings.xml.
     |
    XML
    - Registered: Sun May 05 03:35:11 GMT 2024
    - Last Modified: Mon Jun 19 15:06:01 GMT 2023
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  5. docs/en/data/external_links.yml

    Articles:
      English:
      - author: Kurtis Pykes - NVIDIA
        link: https://developer.nvidia.com/blog/building-a-machine-learning-microservice-with-fastapi/
        title: Building a Machine Learning Microservice with FastAPI
      - author: Ravgeet Dhillon - Twilio
        link: https://www.twilio.com/en-us/blog/booking-appointments-twilio-notion-fastapi
        title: Booking Appointments with Twilio, Notion, and FastAPI
      - author: Abhinav Tripathi - Microsoft Blogs
    Others
    - Registered: Sun May 05 07:19:11 GMT 2024
    - Last Modified: Thu Mar 21 20:57:27 GMT 2024
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  6. docs/pt/docs/async.md

    * **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
    
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    - Last Modified: Thu Apr 18 19:53:19 GMT 2024
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  7. README.md

    researchers push the state-of-the-art in ML and developers easily build and
    deploy ML-powered applications.
    
    TensorFlow was originally developed by researchers and engineers working within
    the Machine Intelligence team at Google Brain to conduct research in machine
    learning and neural networks. However, the framework is versatile enough to be
    used in other areas as well.
    
    TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
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    - Registered: Tue May 07 12:40:20 GMT 2024
    - Last Modified: Thu Oct 05 15:00:10 GMT 2023
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  8. docs/es/docs/async.md

    * **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Imagina en una enorme hoja de cálculo con números y tener que multiplicarlos todos al mismo tiempo.
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  9. 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.
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  10. docs/en/docs/deployment/docker.md

    Linux containers run using the same Linux kernel of the host (machine, virtual machine, cloud server, etc). This just means that they are very lightweight (compared to full virtual machines emulating an entire operating system).
    
    This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).
    
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    - Registered: Sun May 05 07:19:11 GMT 2024
    - Last Modified: Thu May 02 22:37:31 GMT 2024
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