* 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". Piensa en una enorme hoja de cálculo con números y multiplicando todos juntos 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`.

type minioCollector struct {
	desc *prometheus.Desc
}

// Describe sends the super-set of all possible descriptors of metrics
func (c *minioCollector) Describe(ch chan<- *prometheus.Desc) {
	ch <- c.desc
}

// Collect is called by the Prometheus registry when collecting metrics.
func (c *minioCollector) Collect(ch chan<- prometheus.Metric) {
	// Expose MinIO's version information

)

const (
	prometheusMetricsPathLegacy     = "/prometheus/metrics"
	prometheusMetricsV2ClusterPath  = "/v2/metrics/cluster"
	prometheusMetricsV2BucketPath   = "/v2/metrics/bucket"
	prometheusMetricsV2NodePath     = "/v2/metrics/node"
	prometheusMetricsV2ResourcePath = "/v2/metrics/resource"

	// Metrics v3 endpoints
	metricsV3Path = "/metrics/v3"
)

// Standard env prometheus auth type
const (

			aggr.Merge(&disk)
		}
		m.Aggregated.Disk = &aggr
	}

	if types.Contains(madmin.MetricsScanner) {
		metrics := globalScannerMetrics.report()
		m.Aggregated.Scanner = &metrics
	}
	if types.Contains(madmin.MetricsOS) {
		metrics := globalOSMetrics.report()
		m.Aggregated.OS = &metrics
	}
	if types.Contains(madmin.MetricsBatchJobs) {
		m.Aggregated.BatchJobs = globalBatchJobsMetrics.report(opts.jobID)
	}

				MetricV2{
					Description: getMinioProcessIOReadBytesMD(),
					Value:       float64(io.ReadBytes),
				})
		}

		if io.WriteBytes > 0 {
			metrics = append(metrics,
				MetricV2{
					Description: getMinioProcessIOWriteBytesMD(),
					Value:       float64(io.WriteBytes),
				})
		}

		if io.RChar > 0 {
			metrics = append(metrics,
				MetricV2{

	}

	metrics := getHistogramMetrics(ttfbHist, getBucketTTFBDistributionMD(), false, false)
	// additional labels for +Inf for all histogram metrics
	if expPoints := len(labels) * (len(histBuckets) + 1); expPoints != len(metrics) {
		t.Fatalf("Expected %v data points when toLowerAPILabels=false but got %v", expPoints, len(metrics))
	}

	name := rm.Name
	metrics := make([]MetricV2, 0, 3)
	metrics = append(metrics, MetricV2{
		Description:    getResourceMetricDescription(subSys, name, help),
		Value:          rm.Current,
		VariableLabels: cloneMSS(rm.Labels),
	})

	if requireAvgMax {
		avgName := MetricName(fmt.Sprintf("%s_avg", name))
		avgHelp := fmt.Sprintf("%s (avg)", help)
		metrics = append(metrics, MetricV2{

)

// Collector paths.
//
// These are paths under the top-level /minio/metrics/v3 metrics endpoint. Each
// of these paths returns a set of V3 metrics.
//
// Per-bucket metrics endpoints always start with /bucket and the bucket name is
// appended to the path. e.g. if the collector path is /bucket/api, the endpoint
// for the bucket "mybucket" would be /minio/metrics/v3/bucket/api/mybucket
const (