-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`
-   Presubmit jobs (Run on every GitHub PR)
    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

* **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.

    *   Update sklearn imports for deprecated packages.
    *   Deprecate `Variable.count_up_to` and `tf.count_up_to` in favor of
        `Dataset.range`.
    *   Export `confusion_matrix` op as `tf.math.confusion_matrix` instead of
        `tf.train.confusion_matrix`.
    *   Add `tf.dtypes.` endpoint for every constant in dtypes.py. Moving
        endpoints in versions.py to corresponding endpoints in `tf.sysconfig.`

* **Maschinelles Lernen**: Normalerweise sind viele „Matrix“- und „Vektor“-Multiplikationen erforderlich. Stellen Sie sich eine riesige Tabelle mit Zahlen vor, in der Sie alle Zahlen gleichzeitig multiplizieren.

* 🔧 Update MkDocs for other languages. PR [#9734](https://github.com/tiangolo/fastapi/pull/9734) by [@tiangolo](https://github.com/tiangolo).
* 👷 Refactor Docs CI, run in multiple workers with a dynamic matrix to optimize speed. PR [#9732](https://github.com/tiangolo/fastapi/pull/9732) by [@tiangolo](https://github.com/tiangolo).

jetzt

// jewelry : 2015-03-05 Binky Moon, LLC
jewelry

// jio : 2015-04-02 Reliance Industries Limited
jio

// jll : 2015-04-02 Jones Lang LaSalle Incorporated
jll

// jmp : 2015-03-26 Matrix IP LLC
jmp

// jnj : 2015-06-18 Johnson & Johnson Services, Inc.
jnj

// joburg : 2014-03-24 ZA Central Registry NPC trading as ZA Central Registry
joburg

etc
ets
fins
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ho
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iguals
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les
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llavors
m'he
ma
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mateix
mateixa
mateixes
mateixos
me
mentre
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meu
meus
meva
meves
molt
molta
moltes
molts
mon
mons
n'he
n'hi
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ni
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només

### Workloads that saturate nodes with pods may see pods that fail due to node admission

* **Bilgisayar görüsü**: bir görüntü milyonlarca pikselden oluşur, her pikselin 3 değeri / rengi vardır, bu pikseller üzerinde aynı anda bir şeyler hesaplamayı gerektiren işleme.
* **Makine Öğrenimi**: Çok sayıda "matris" ve "vektör" çarpımı gerektirir. Sayıları olan ve hepsini aynı anda çarpan büyük bir elektronik tablo düşünün.