资源列表
KRR
- 核岭回归算法 输入数据集(需要分开存放训练集和测试集) 利用4重交叉验证法调参 最后输出分类准确率(Kernel ridge regression algorithm Input data set (training set and test set need to be stored separately) Parameter adjustment by 4-fold cross validation Final output classification accuracy)
CNN_sentence_tensorflow-master
- 基于卷机神经网络的文本信息提取应用的设计与实现，cn(Design and Implementation of Text Information Extraction Application Based on Reel Neural Network)
程序（分享）
- matalb2020a深度学习 学习程序整理，适合入门(matlab deeplearning toolbox my experience)
ADP冲冲冲
- 基于bp神经网络的adp小程序，无具体数值，需自行添加，包含actor网络和critic网络(The ADP program based on BP neural network has no specific value and needs to be added by itself, including actor network and critical network)
2016-deep learning
- deep learning英文电子版pdf，深度学习不错的书籍(Deep learning English electronic PDF, good books for deep learning)
Matlab偏最小二乘法用于判别分析
- MATLAB偏最小二乘法用于判别分析，亲测可用(The partial least squares method of MATLAB is used for discriminant analysis, and the pro-test is available.)
强化学习
- 使用强化学习实现策略梯度和和马尔科夫决策过程(Implementing Strategic Gradient Sum and Markov Decision Process with Reinforcement Learning)
bp参数辨识
- 锂离子电池参数辨识，把各个参数作为bp神经网络的权重阀值进行学习(Parameter identification of lithium-ion batteries and learning of each parameter as the weight threshold of BP neural network)
李宏毅—1天搞懂深度学习
- 本文是2016 台湾资料科学年会前导课程“一天搞懂深度学习”的全部讲义PPT（共268页），由台湾大学电机工程学助理教授李宏毅主讲。作者在文中分四个部分对神经网络的原理、目前存在形态以及未来的发展进行了介绍。深度学习的每一个核心概念在文中都有相关案例进行呈现，通俗易懂。一天的时间搞懂深度学习？其实并不是没有可能。(This is the entire handout PPT (268 pages in total) of "a day to understand deep learni
code
- 利用python编写室内定位机器学习，计算结果，室内定位(Indoor Localization by wifi)
花的分类问题
- 神经网络是一组连接的输入/输出单元，其中每个连接都与一个权重相关联。在学习阶段，通过调整这些权重，能够预测输入元素的正确类标号(A neural network is a set of connected input/output units, where each connection is associated with a weight. In the learning phase, by adjusting these weights, the correct class label o
RBF
- 径向基函数神经网络，基本算例.........(radial basis function)