本教程展示如何运用TensorFlow与Matplotlib（plt）来重现学术研究中常见的损失函数及精度变化曲线。通过实例解析，帮助读者掌握数据可视化技能，加深对模型训练过程的理解。
直接上代码：
```python
fig_loss = np.zeros([n_epoch])
fig_acc1 = np.zeros([n_epoch])
fig_acc2 = np.zeros([n_epoch])
for epoch in range(n_epoch):
start_time = time.time() # 记录开始时间
train_loss, train_acc, n_batch = 0, 0, 0
for x_train_a, y_train_a in minibatches(x_train, y_train, batch_size, shuffle=True):
_, error_rate = model.train_on_batch(x_train_a, y_train_a)
```
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