code: '''
  This is a script to train a model with a variety of estimators
  '''
  import pickle
  import pandas as pd
  from sklearn.neural_network import MLPRegressor
  from config import Config
  
  # Creating a path to save our model
  Config.models_path.mkdir(parents=True, exist_ok=True)
  
  # Loading the training and testing features into a pandas DataFrame
  x_train = pd.read_csv(str(Config.features_path / 'train_features.csv'))
  y_train = pd.read_csv(str(Config.features_path / 'train_target.csv'))
  
  # Instantiating and fitting the algorithm
  model = MLPRegressor(max_iter=800, alpha=0.4371)
  model = model.fit(x_train, y_train.to_numpy().ravel())
  
  # Saving the model into a pickle file
  pickle.dump(model, open('model.pickle', 'wb'))
  
apis: sklearn.neural_network.MLPRegressor