> For the complete documentation index, see [llms.txt](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-san-men-ke-jie-gou-hua-ji-qi-xue-xi-xiang-mu-structuring-machine-learning-projects/di-san-men-ke-structuring-machine-learning-projects/di-yi-zhou-ml-strategy/111-chao-guo-ren-de-biao-xian-ff08-surpassing-human-level-performance.md).

# 1.11 超过人的表现（Surpassing human- level performance）

对于自然感知类问题，例如视觉、听觉等，机器学习的表现不及人类。但是在很多其它方面，机器学习模型的表现已经超过人类了，包括：

* **Online advertising**
* **Product recommendations**
* **Logistics(predicting transit time)**
* **Loan approvals**

机器学习模型超过human-level performance是比较困难的。但是只要提供足够多的样本数据，训练复杂的神经网络，模型预测准确性会大大提高，很有可能接近甚至超过human-level performance。值得一提的是当算法模型的表现超过human-level performance时，很难再通过人的直觉来解决如何继续提高算法模型性能的问题

![](/files/-Le0cb25_NkNlI55VgrC)![](/files/-Le0cb27Fj-sbc-lCp_6)