资源列表
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)
人工神经网络
- 基于MATLAB的人工神经网络学习，内涵代码和案例数据(Artificial neural network learning based on MATLAB, connotation code and case data)
垃圾短信分类
- 基于文本内容的垃圾短信识别,对数据进行了数据清洗,分词等,进行 了模型训练及评价(Based on the text content of spam short message recognition, data cleaning, segmentation, model training and evaluation are carried out)
cartographer--zhushi
- cartographer是一个系统，提供实时同步定位和测绘(SLAM)在二维和三维跨多个平台和传感器配置。(Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.)
rbf500
- RBF神经网络建模，也可适用于多输入多输出(RBF neural network modeling can also be applied to multi input and multi output)
神经网络基础
- 神经网络基础ppt,课件来源于吴恩达老师深度学习课程课件(Ppt of neural network foundation, the courseware comes from the courseware of in-depth learning of teacher Wu enda)
主动半监督K_means聚类算法研究及应用_吕峰.caj
- 基于师生模型实现半监督学习，百万级数据级(Semi supervised learning based on teacher-student model, million data level)