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supervised learning.ipynb 983 B

6 years ago
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  7. "# Supervised learning\n"
  8. ]
  9. },
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  14. "## References\n",
  15. "* [Supervised learning: predicting an output variable from high-dimensional observations](http://scikit-learn.org/stable/tutorial/statistical_inference/supervised_learning.html)\n",
  16. "* [A tutorial on statistical-learning for scientific data processing](http://scikit-learn.org/stable/tutorial/statistical_inference/index.html)"
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机器学习越来越多应用到飞行器、机器人等领域,其目的是利用计算机实现类似人类的智能,从而实现装备的智能化与无人化。本课程旨在引导学生掌握机器学习的基本知识、典型方法与技术,通过具体的应用案例激发学生对该学科的兴趣,鼓励学生能够从人工智能的角度来分析、解决飞行器、机器人所面临的问题和挑战。本课程主要内容包括Python编程基础,机器学习模型,无监督学习、监督学习、深度学习基础知识与实现,并学习如何利用机器学习解决实际问题,从而全面提升自我的《综合能力》。