基于人工智能的应用于研究生管理信息系统的开发与实现

import pandas as pd

# 加载历史选课数据

data = pd.read_csv('student_courses.csv')

print(data.head())

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from sklearn.model_selection import train_test_split

from sklearn.ensemble import RandomForestClassifier

# 数据预处理

X = data[['grade', 'major']]

y = data['course_id']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# 训练模型

model = RandomForestClassifier()

model.fit(X_train, y_train)

predictions = model.predict(X_test)

print(predictions)

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from flask import Flask, jsonify

app = Flask(__name__)

@app.route('/recommend/', methods=['GET'])

def recommend(student_id):

# 这里可以调用上面训练好的模型

recommendation = {'course': 'Math 401'}

return jsonify(recommendation)

if __name__ == '__main__':

app.run(debug=True)

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