资源列表
lfm
- 重叠社区发现LFM算法，基于python实现，导入的文件是lfr基准测试网络，里面写了检测指标，文件可更改，算法通过网络邻接矩阵来实现社区划分(The overlapping community found the LFM algorithm, based on the python implementation, the imported document is the LFR benchmark network, in which the detection index is written
bp和maltab的车牌识别
- 实现了灰度处理，锐化，边缘检测，神经网络(Grayscale processing, sharpening, edge detection, neural network)
dstar-lite-master
- 基于dijikstra和A*算法的改进A*算法，能在路径规划的各阶段更新节点信息，规划新的路径(The improved A* algorithm based on dijikstra and A* algorithm can update node information in all stages of path planning and plan new path.)
naive_bayes（简单贝叶斯）
- 简单贝叶斯的介绍和讲解，深刻理解简单的贝叶斯(Simple introduction and explanation of Bias, a deep understanding of simple Bias.)
5、贝叶斯python代码及数据
- 贝叶斯算法实现分类及数据集 python代码 分类算法(The classification and data set of Bias algorithm)
cudnn-7.5-windows10-x64-v5.0-ga
- cudnn 5.0 匹配cuda7.5，安装GPU支持的深度学习的伙伴用得着。这是cudnn的版本5.0，可以配合Cuda7.5使用。(Cudnn 5 matches cuda7.5, and it is useful for GPU to support deep learning partners. This is the version 5 of cudnn, which can be used in conjunction with Cuda7.5.)
LSTM-morevalible
- LSTM 多变量预测，天气等影戏因素，可以执行，完全可以执行，思想也很简单(LSTM multivariable prediction)
code
- Q-learning 算法实现AGV的最优路径规划，实测效果非常好，对于研究深度学习和强化学习的同学很有帮助！(The Q-learning algorithm realizes the optimal path planning of AGV, and the measured results are very good. It is very helpful for students who are studying deep learning and reinforcement learn
机器学习算法PPT
- 机器学习课件 从基础入门到深度学习 很详细(Machine learning courseware)
VMD
- 使用可变模式分解的神经网络预测模型，可用于风速、电价预测等等。(Neural network prediction model using variable pattern decomposition can be used for wind speed, price forecasting and so on.)
astar
- A*算法实现路径规划，返回的是离散的路径点，为启发式算法(Path planning by A* algorithm)
LSTM
- LSTM对价格的预测 利用最新的神经网络 希望大家能够喜欢(29/5000 The LSTM's prediction of prices USES the latest neural networks to please everyone)