资源列表
CNN
- CNN contains the desiption of the structure and usage the algorithm
BP
- 利用BP神经网络实现 鸢尾花数据分类(Data classification of iris using BP neural network)
搜索排序模型
- 介绍了搜索排序中的树模型，循序渐进，附详实的数学公式推导。(The tree model in search ranking is introduced, and the mathematical formula is deduced in detail.)
Sciprts
- 用 dataset3 作为训练数据，用 dataset4 作为测试数据，采用不同的特征、训练样本数、分类方法进行比较实验，观察、分析实验结果的异同。 训练分类器的方法为最小错误率贝叶斯分类器（假设正态分布，先验概率各 50%）。使用Bayesscr ipt.m运行代码。(Using dataset3 as training data, dataset4 is used as test data, and different characteristics, training samples an
ID3firstExample
- sample work with id3 decision tree
ABC_cobe
- 人工智能蜂群算法，c++编辑，是用软件Notepad++存储的，可自行更改(Artificial intelligence bee colony algorithm, c++ editor, is stored in software Notepad++ and can be changed by itself)
Tensorflow 实战Google深度学习框架
- 深度学习框架，适合人工智能学习以及刚入门的知识普及(Deep Learning Framework)
SAGAexp.m
- 遗传算法和模拟退火算法融合，解决遗传算法早熟问题。(Fusion of genetic algorithm and simulated annealing algorithm)
bignum (3)
- bignum encryption library 2
MINIST
- mnist库上 应用DBN网络 DBN使用RBM结构，半监督网络，逐层训练(Application on the DBN network)
generative-models-master
- 生成对抗网络中的各种衍生网络结构，包括基础GAN，C-GAN,AC-GAN等等 变分自动编码器各种衍生网络结构，包括条件变分自动编码器等等(Generated in the network against the derivative network structure, including GAN, C-GAN, AC-GAN and so on. The variational autocoder derivative network structure, including con
机器学习实战.pdf
- 一本适合机器学习入门的书籍，包含大量流行的机器学习算法和python实现(A book suitable for machine learning, including a large number of popular machine learning algorithms and python implementation)