Update README.md

README.md

@@ -15,34 +15,47 @@ Model
 The machine learning model uses a decision tree algorithm to predict student enrollment. The model has been trained on the dataset using 80% of the data for training and 20% for testing. The accuracy of the model is 85%.
 
 Files
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 This repository contains the following files:
 
 enrollment_prediction_model.ipynb: Jupyter notebook containing the code for training and testing the model
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 enrollment_prediction_model.pkl: Serialized machine learning model file
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 enrollment_prediction_model_readme.md: Readme file containing information about the machine learning model
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 Usage
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 To use the machine learning model, follow these steps:
 
 Clone the repository
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 Install the required packages (pandas, numpy, scikit-learn)
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 Load the serialized machine learning model from the enrollment_prediction_model.pkl file
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 Prepare a new dataset with the same columns as the original dataset
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 Use the predict function of the model to predict enrollment for each row in the new dataset
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 Example code:
 
-python
-Copy code
 import pandas as pd
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 import pickle
 
 # Load serialized machine learning model
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 with open('enrollment_prediction_model.pkl', 'rb') as file:
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     model = pickle.load(file)
 
 # Prepare new dataset
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 new_data = pd.read_csv('new_data.csv')
 
 # Predict enrollment
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 predictions = model.predict(new_data)