【推荐系统】TensorFlow手动实现AutoRec基于协同过滤

• 一、导包
• 二、加载数据
• 三、构建模型
• 四、训练数据
• 五、预测结果

import pathlib

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

import tensorflow as tf

from tensorflow import keras
from tensorflow.keras import layers

import numpy as np

# 100个用户，300个物品
data = pd.Dataframe(np.random.randint(5, size=(100, 300)))

def build_model():
    model = keras.Sequential([
        layers.Dense(100, activation = 'relu', input_shape=[100]),
        layers.Dense(100, activation = 'relu'),
    ])
    
    optimizer = tf.keras.optimizers.RMSprop(0.001)
    
    model.compile(loss = 'mse',
                 optimizer = optimizer,
                 metrics = ['mae', 'mse'])
    
    return model

model = build_model()
model.summary()

train_data = data.T
EPOCHS = 500

model.fit(train_data,
           train_data,
           epochs = EPOCHS,
           validation_split = 0.1,
           verbose = 0)

pd.Dataframe(model.predict(train_data).T)