统一消息系统

import pandas as pd

def preprocess_data(file_path):

df = pd.read_csv(file_path)

# 清洗数据

df.dropna(inplace=True)

return df

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from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense

def build_model(input_dim):

实训实习管理系统

model = Sequential()

model.add(Dense(64, input_dim=input_dim, activation='relu'))

model.add(Dense(32, activation='relu'))

model.add(Dense(1, activation='sigmoid'))

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

return model

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from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route('/classify_message', methods=['POST'])

def classify_message():

data = request.json

preprocessed = preprocess_data(data['file_path'])

prediction = model.predict(preprocessed)

response = {'message_type': 'spam' if prediction > 0.5 else 'normal'}

return jsonify(response)

if __name__ == '__main__':

app.run(debug=True)

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