搜索资源列表
Lenetchange
- 卷积神经网络CNN，基于手写体数据库的相关训练(Convolution neural network, handwriting training)
Training
- 极限学习机的回归拟合——对比实验研究，改进BP算法的一些缺点，在ELM算法的基础上进行回归拟合预测。(Regression fitting Some shortcomings of BP algorithm are improved, and regression fitting prediction is carried out on the basis of ELM algorithm.)
bp2
- 用MATLAB 实现对不同种类的饮料或者果汁的分类，通过训练学习，再进行预测，可以得到分类的正确率(The classification of different kinds of drinks or fruit juice is realized by MATLAB, and the correct rate of classification can be obtained by training, learning and forecasting)
DBN的matlab代码
- 这是一个关于用数字识别训练一个手写数字识别的深度神经网络事例(This is a deep neural network example that uses digital recognition to train a handwritten numeral recognition)
计算机技能训练最终版（C语言） - 副本
- 在学习和掌握C语言之后，开展了C语言课设——设计和实现实现学生成绩管理系统，程序还不算完善，请谅解(After learning and mastering C language, the C language course has been set up to design and implement the student achievement management system. The procedures are not perfect, please understand)
Altium_designer_PCB训练手册
- Altium 的训练手册，推荐入门者学习！(Altium Designer manual)
bppid_S函数
- bp神经的S型函数，开发与matlab平台，可以借用于相关算法的训练学习。(BP neural S function, developed and MATLAB platform, can be used for the training of related algorithms learning.)
bp-分类器
- 这是bp神经网络的M文件，包括BP网络的第一阶段学习期（训练加权系数wki，wij)，BP网络的第二阶段工作期（根据局训练好的wki，wij和给定的输入计算输出），程序里有详细注释。该程序被用来作为分类器使用。(This is the BP neural network M files, including the first phase of BP network learning period (training weighting coefficient wki, wij), the se
深度卷积神经网络
- 作为类脑计算领域的一个重要研究成果，深度卷积神经网络已经广泛应用到计算机视觉、自然语言处理、信息检索、语音识别、语义理解等多个领域，在工业界和学术界掀起了神经网络研究的浪潮，促进了人工智能的发展。卷积神经网络直接以原始数据作为输入，从大量训练数据中自动学习特征的表示。(As the important research achievement, deep convolutional neural networks have been widely applied to various fiel
jtold
- 介绍了基于分解思想的支持向量机的训练算法,()
Knn_train_mnist
- 利用Python实现Mnist数据集训练knn算法(Use Knn method to train mnist.)
encode-xunlian(1)r
- 从给定的很多张自然图片中截取出大小为8*8的小patches图片共10000张，现在需要用sparse autoencoder的方法训练出一个隐含层网络所学习到的特征。该网络共有3层，输入层是64个节点，隐含层是25个节点，输出层当然也是64个节点了。这里只是上传了训练的部分代码，后续继续(A total of 10000 small patches pictures with size 8*8 are extracted from a lot of natural pictures. Now
636614
- 使用遗传算法对BP网络权值阈值进行优化,再用BP算法训练网络()
962569
- 通过已知的先验概率,在输入训练序列之后,可以对数值进行判别是属于哪一类的数据,简单可以应用于模式识别()
bp
- 新手入门推荐：神经网络代码,根据神经网络来训练学习，将一些不同的数据挑选，训练成合适的数据，根据这些数据可以预测之后的会产生的新数据(Neural network code, based on neural network training learning, will pick up some different data and train them into suitable data. According to these data, we can predict the new dat
纯C-CNN
- 纯C深度学习库，里面包含MNIST手写数字识别数据集，编译就能训练和预测(Pure C depth learning library, which contains MNIST handwritten digital recognition data sets, compiling can be trained and predicted.)
学习程序样例
- 演示模型便展示了一学习算法的训练结果，它非常生动地、系统地复现了生物神经网络的活动。(The demonstration model shows the training results of a learning algorithm, which vividly and systematically recombines the activities of the biological neural network.)
ym_model
- 本项目包括XGB模型训练所需的数据，etl代码，模型训练代码(This project includes the data required for XGB model training, etl code, model training code)
情感分析
- 分类，用于对情感词的统计、排序、分类等 包括源程序、数据拆分程序、训练集和测试集(Classification for statistics, sorting and classification of emotional words Includes source programs, data split programs, training sets, and test sets)
deepdesc-release-master
- 利用深度学习对特征描述符进行训练，得到较精确的特征描述符(The feature descr iptors are trained by depth learning to obtain more accurate feature descr iptors)