O que eu consigo fazer

from sklearn.pipeline import Pipeline
from sklearn.ensemble import RandomForest

pipe = Pipeline([
  ('scaler', StandardScaler()),
  ('model', RandomForest(
    n_estimators=200
  ))
])
pipe.fit(X_train, y_train)
# Acurácia: 97.3%

const useDebounce = <T>(
  value: T, delay: number
): T => {
  const [v, setV] = useState(value)
  useEffect(() => {
    const t = setTimeout(
      () => setV(value), delay
    )
    return () => clearTimeout(t)
  }, [value, delay])
  return v
}

WITH cohort AS (
  SELECT user_id,
    DATE_TRUNC('month',
      created_at) AS cohort_month,
    SUM(revenue) OVER (
      PARTITION BY user_id
      ORDER BY created_at
    ) AS ltv
  FROM orders
)
SELECT * FROM cohort
WHERE ltv > 1000

#!/bin/bash
deploy() {
  echo "🚀 Deploying v$VERSION"
  docker build -t app:$VERSION .
  if ! docker push app:$VERSION; then
    rollback $PREV_VERSION
    notify_slack "❌ Failed"
    exit 1
  fi
  notify_slack "✅ Done"
}
deploy