We are using Python 3.11-slim in our case.
Step-by-Step Guide to Deploying ML Models with Docker

Let’s walk through how to deploy a machine-learning model using Docker.
 model.py:


from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
import pickle


# Train and save the model
def train_model():
    # Load dataset
    data = load_iris()
    X, y = data.data, data.target

    # Train model
    model = RandomForestClassifier()
    model.fit(X, y)
for more:https://cuty.io/Lkw5k1