资源列表
大数据下的机器学习算法综述
- 研究大数据环境下的机器学习算法成为学术界和产业界共同关注的话题. 文中主要分析和总结当前用于处理大数据的机器学习算法的研究现状.(Developing machine learning algorithms for big data is a research focus. In this paper, the state of the art machine learning techniques for big data are introduced and analyzed.)
resnet-protofiles-master
- 卷积神经网络resnet18、resnet34、resnet50、resnet101、resnet152的配置文件（网络结构和解决方案文件）(Convolution neural network resnet18, resnet34, resnet50, resnet101, resnet152 configuration file (network structure and solution file))
DSI
- 一个很好用的DS证据理论工具箱，可以实现算法编程以及各种应用(A good toolbox of DS evidence theory)
rbf
- 自己编写RBF神经网络程序，RBF神经网络隐层采用标准Gaussian径向基函数，输出层采用线性激活函数，其中数据中心、扩展常数和输出权值均用梯度法求解，它们的学习率均为0.001。其中隐节点数选为10，初始输出权值取[-0.1，0.1]内的随机值，初始数据中心取[-1，1]内的随机值，初始扩展常数取[0.1，0.3]内的随机值，输入采用[0 1]的随机阶跃输入(Write your own RBF neural network, RBF neural network hidden layer
梯度下降
- 这是一篇精华文章，详细的说明了深度学习梯度下降算法的思想，并附有程序结果。(This is an essence of the article, detailed descr iption of the depth of learning, gradient descent algorithm ideas, along with program results.)
专家系统11本
- 专家系统人工智能方面的经典书籍11本打包压缩的，适合对专家系统感兴趣的本科及研究生，以及工程技术人员(Expert systems, artificial intelligence in the classic books, 11 packaged, compressed, suitable for the undergraduate and graduate students interested in expert systems, as well as engineering and te
Project1
- 多层神经网络，在训练过程中采用自适应学习率Adagrad方法。可以实现回归或分类问题。(The adaptive learning rate Adagrad method is adopted in the training process of the multilayer neural network. Regression or classification problems can be achieved.)
面向机器智能的TensorFlow实践
- 适合作为Tensorflow学习的入门书籍，很多基本概念讲的比较清楚(Suitable for Tensorflow as an introduction to learning books, explain many basic concepts more clear)
STDP_simulations
- 仿真实现STDP的波形，《STDP as presynaptic activity times rate of change of postsynaptic activity》代码。(STDP implemented on python, code in "STDP as presynaptic activity times rate of change of postsynaptic activity", arXiv:1509.05936v2.)
Helicopter
- 模拟直升机案例，供研究学习各种飞行控制方法使用(Simulated helicopter case)
Practice_03
- 深度学习,基于python的机器学习，包括挖掘之类(deep learningDepth learning, Python based machine learning, including mining and the like)
聚类算法
- 聚类算法,介绍聚类算法的原理以及应用！原理的推导，以及聚类算法应用的实例。包括迭代过程，已经迭代停止条件。(Clustering Algorithm)