input: from typing import Any
  
  def predict_LTV(customer_input: Any) -> float:
      """ A machine learning model that predicts customer lifetime value given a customer's past transactions.
      >>> predict_LTV([[10,100,5]])
      1234.56 # example output
      """
      import pandas as pd
      import numpy as np
      from sklearn.preprocessing import StandardScaler
      from sklearn.ensemble import RandomForestRegressor
      
      df = pd.read_csv('transactions.csv')
      X = df.iloc[:,:-1].values
      y = df.iloc[:,-1].values
      scaler = StandardScaler()
      X = scaler.fit_transform(X)
      
      model = RandomForestRegressor()
      model.fit(X, y)
      
      customer_input_scaled = scaler.transform(customer_input)
      predicted_LTV = model.predict(customer_input_scaled)[0]
      return predicted_LTV
output:     return 1234.56