搜索资源列表
Kmeans
- 《视觉机器学习20讲配套仿真代码》——1、K-means学习-" Vision Machine Learning Lecture 20 supporting the simulation code" 1, K-means learning
Adaboost
- 《视觉机器学习20讲》的配套仿真代码——Adaboost分类算法，可运行，有注释-The visual machine learning about 20 supporting simulation code- Adaboost classification algorithm, can run, with comments
BP
- 《视觉机器学习20讲》配套仿真代码—bp神经网络，有注释，适合初学者-The visual machine learning about 20 matching simulation code- bp neural network, with comments, suitable for beginners
CNN
- <\视觉机器学习20讲>配套仿真代码——CNN，卷积神经网络，有注释，适合初学者-Visual simulation code CNN, form a complete set of machine learning about 20 convolutional neural networks, have comments, suitable for beginners
deeplearn
- <视觉机器学习20讲>配套仿真代码——深度学习，有注释，适合初学者-< visual machine learning speak > 20 matching simulation code- deep learning, there are comments, suitable for beginners
EM
- 《视觉机器学习20讲》的配套仿真代码——EM算法 均值最大算法，适合初学者-The visual machine learning about 20 supporting simulation code- EM algorithm average maximum algorithm, suitable for beginners
Regression-learning
- 一个回归学习的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-A return to learn the Matlab routines, can be run directly, the specific content of reference books < visual machine learning 20
Random-Forest
- 一个random forest的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-Forest MATLAB of a random routine, you can run directly, the specific content of reference books < visual machine learning 20
Bayesian-learning-
- 一个贝叶斯学习的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-A Bayesian learning matlab routines, you can run directly
EM-learning
- 一个em学习的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-A EM learning matlab routines, you can run directly, the specific content of reference books < visual machine learning 20
视觉机器学习20讲
- 《视觉机器学习20讲》，随书附带的所有matlab源代码(20 lectures of machine learning , source code)