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适用场景：

1. 机器学习研究：算法研究 、模型开发

2. 企业AI应用开发：模型训练流程管理、实验结果对比、模型迭代优化

3. 教育科研机构：深度学习实验、科研项目管理、实验数据分析

系统截图：

核心代码：

from flask import render_template, request, jsonify
from app import app
from app.utils.data_import import import_dataset
from app.utils.data_cleaning import clean_data
from app.utils.model_training import train_model
from app.utils.anomaly_detection import detect_anomalies@app.route('/')
@app.route('/home')
def home():return render_template('home.html')@app.route('/data-import', methods=['GET', 'POST'])
def data_import_route():if request.method == 'POST':# 处理数据导入逻辑passreturn render_template('data_import.html')@app.route('/data-cleaning', methods=['GET', 'POST'])
def data_cleaning_route():if request.method == 'POST':# 处理数据清洗逻辑passreturn render_template('data_cleaning.html')@app.route('/model-training', methods=['GET', 'POST'])
def model_training_route():if request.method == 'POST':# 处理模型训练逻辑passreturn render_template('model_training.html')@app.route('/anomaly-detection', methods=['GET', 'POST'])
def anomaly_detection_route():if request.method == 'POST':# 处理异常检测逻辑passreturn render_template('anomaly_detection.html')