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README.md 920 B

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  1. ## References
  2. * [code of book "Learn Deep Learning with PyTorch"](https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch)
  3. * [PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation](https://github.com/chenyuntc/pytorch-book)
  4. * [Awesome-Pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list)
  5. * [PyTorch Tutorial for Deep Learning Researchers](https://github.com/yunjey/pytorch-tutorial)
  6. * [The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.](https://github.com/ritchieng/the-incredible-pytorch)
  7. * [Simple examples to introduce PyTorch](https://github.com/jcjohnson/pytorch-examples)
  8. * [Simple PyTorch Tutorials Zero to ALL!](https://github.com/hunkim/PyTorchZeroToAll)
  9. * [从基础概念到实现,小白如何快速入门PyTorch](https://mp.weixin.qq.com/s/zhkaenFdnB5KgaEYb-XDEQ)

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》。