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Shuhui Bu
c9f79e6799
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7 years ago | |
|---|---|---|
| 0_numpy_matplotlib_scipy_sympy | 7 years ago | |
| 0_python | 7 years ago | |
| 1_kmeans | 7 years ago | |
| 1_knn | 7 years ago | |
| 1_logistic_regression | 7 years ago | |
| 1_nn | 7 years ago | |
| 2_pytorch | 7 years ago | |
| data | 7 years ago | |
| demo_code | 7 years ago | |
| references | 7 years ago | |
| tips | 7 years ago | |
| .gitignore | 7 years ago | |
| LICENSE | 7 years ago | |
| README.md | 7 years ago | |
| References.md | 7 years ago | |
| requirements.txt | 7 years ago | |
README.md
Python与机器学习
本教程包含了一些使用Python来学习机器学习的notebook，通过本教程能够引导学习Python的基础知识和机器学习的理论知识和实际编程，并学习如何解决实际问题。
由于本课程需要大量的编程练习才能取得比较好的学习效果，因此需要认真把作业和报告完成。作业的地址是：https://gitee.com/machinelearning2018/pr_homework 请按照里面的说明进行操作。
内容
- Python
- numpy & matplotlib
- knn
- kMenas
- Logistic Regression
- Neural Network
- PyTorch
- short tutorial
- basic/Tensor-and-Variable
- basic/autograd
- basic/dynamic-graph
- nn/linear-regression-gradient-descend
- nn/logistic-regression
- nn/nn-sequential-module
- nn/bp
- nn/deep-nn
- nn/param_initialize
- optim/sgd
- optim/adam
- optim/adam
- cnn/basic_conv
- cnn/batch-normalization
- cnn/regularization
- cnn/lr-decay
- cnn/vgg
- cnn/googlenet
- cnn/densenet
- cnn/resnet
- rnn/pytorch-rnn
- rnn/rnn-for-image
- rnn/lstm-time-series
- gan/autoencoder
- gan/vae
- gan/gan
其他参考
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》。
Jupyter Notebook SVG Python CSV Text other