* 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.

* **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.

### Major Features and Improvements

*   Added F-Score metrics `tf.keras.metrics.FBetaScore`, `tf.keras.metrics.F1Score`, and `tf.keras.metrics.R2Score`.
*   Added activation function `tf.keras.activations.mish`.

1. Start a distributed MinIO instance (4 nodes setup)
2. Start Prometheus server and AlertManager
3. Bring down couple of MinIO instances to bring down the Erasure Set tolerance to -1 and verify the same with `mc admin prometheus metrics ALIAS | grep minio_cluster_health_erasure_set_status`
4. Wait for 5 mins (as alert is configured to be firing after 5 mins), and verify that you see an entry in webhook for the alert as well as in Prometheus console as shown below

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ho
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igual
iguals
ja
l'hi
la
les
li
li'n
llavors
m'he
ma
mal
malgrat
mateix
mateixa
mateixes
mateixos
me
mentre
més
meu
meus
meva
meves
molt
molta
moltes
molts
mon
mons
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n'hi
ne
ni
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només
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nostra

has been deprecated as part of the deprecation of Heapster. Instead, you may use the [metrics server](https://github.com/kubernetes-incubator/metrics-server). It's a simplified heapster that is able to gather and serve current metrics values. It provides the Metrics API that is used by `kubectl top`, and horizontal pod autoscaler. Note that it doesn't include some features of Heapster, such as short term metrics for graphs in kube-dashboard and dedicated push sinks, which proved hard to maintain and...

* Flex drivers by default do not produce metrics. Flex plugins can enable metrics collection by setting  the capability 'supportsMetrics' to true. Make sure the file system can support fs stat to produce metrics in this case. ([#67508](https://github.com/kubernetes/kubernetes/pull/67508), [@brahmaroutu](https://github.com/brahmaroutu))

pkg runtime/metrics, const KindBad = 0
pkg runtime/metrics, const KindBad ValueKind
pkg runtime/metrics, const KindFloat64 = 2
pkg runtime/metrics, const KindFloat64 ValueKind
pkg runtime/metrics, const KindFloat64Histogram = 3
pkg runtime/metrics, const KindFloat64Histogram ValueKind
pkg runtime/metrics, const KindUint64 = 1
pkg runtime/metrics, const KindUint64 ValueKind

      - [Storage](#storage)
    - [Deprecations and Removals](#deprecations-and-removals)
    - [Metrics Changes](#metrics-changes)
      - [Added metrics](#added-metrics)
      - [Removed metrics](#removed-metrics)
      - [Deprecated/changed metrics](#deprecated/changed-metrics)
    - [Notable Features](#notable-features)
      - [Beta](#beta)
      - [Alpha](#alpha)

### Pod resource metrics

On-demand metrics calculation is now available through `/metrics/resources`. [When enabled](
https://docs.k8s.io/concepts/cluster-administration/system-metrics#kube-scheduler-metrics), the endpoint will report the requested resources and the desired limits of all running pods.

### Introducing `RootCAConfigMap`