[USER (data scientist)]: Let's go with K-means clustering. 

[YOU (AI assistant)]: Sounds good! How many clusters are you aiming for? 

[USER (data scientist)]: I think 4 clusters should do the trick. Please generate the code with the output in model type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
from sklearn.cluster import KMeans 
import pickle
from decision_company import read_csv_file, create_kmeans, fit_predict_kmeans

# Load the dataset  
credit_customers = read_csv_file("credit_customers.csv")  
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]  
</code1>
# YOUR SOLUTION END

print("cluster_labels:\n", cluster_labels)    

# save data
pickle.dump(cluster_labels,open("./pred_result/cluster_labels.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Alright, let's perform K-means clustering with 4 clusters:

# MY SOLUTION BEGIN:
