资源列表
qwe
- 神经网络中网络结构哦、初始连接权值和阈值的选择对网络训练的影响很大，用遗传算法的神经网络进行优化。(The choice of network structure, initial connection weight and threshold in neural network has a great influence on network training, and is optimized by the neural network of genetic algorithm.)
dfa.py
- dfa 验证机，可以用于AI校验，敏感词校验，以及机器学习(dfa verification machine)
决策树-判断隐形眼镜的类型
- 使用python实现的利用随机数生成算法对一个实例，判断隐形眼镜类型的分类问题进行解决。(Use python and random decision tree algorithm to solve the classification problem)
Matlab神经网络工具箱应用简介
- 学习人工智能编程的学习资料很不错，欢迎下载(Learning the learning materials of artificial intelligence programming is very good)
mnist
- 使用了全连接网络，卷积神经网络，循环神经网络分别构建不同的分类器，如何通过模型保存原理进行保存。(Using the fully connected network and convolution neural network, recurrent neural network builds different classifiers respectively, and how to save them through the preservation principle of the mode
机器学习pics
- 17张思维导图+1张机器学习图，每张图都很有指导价值(17 thinking map +1 machine learning diagram)
基于bp神经网络的孤立词识别
- 利用MATLAB，实现对一些孤立词的识别。语音识别的一种(bp matlab recongnation)
Clustering-master
- 一个基础的聚类算法，带数据集，适合初步研究聚类算法的人学习。(A basic clustering algorithm, with data sets, is suitable for the preliminary study of clustering algorithm for human learning.)
spr-7
- 采用两线程随机离散卷积神经网络针对触觉序列进行特征提取与分类。(Two thread random discrete convolution neural network is applied to feature extraction and classification for haptic sequences.)
Python网络数据采集
- Python网络数据采集，适合想要学习使用Python进行网络数据采集的人。(Python network data collection for those who want to learn how to use Python for network data acquisition.)
LT-9
- 两线程随机离散卷积神经网络，针对LT-9数据集。(Two thread random discrete convolution neural network for LT-9 data set.)
生成对抗网络
- 生成对抗网络针对mnist数据集，Python语言实现。(Generate confrontation network for MNIST data set, implemented in Python language.)