采用Text_CNN进行文本分类

说明：  飞桨(PaddlePaddle)是集深度学习核心框架、工具组件和服务平台为一体的技术先进、功能完备的开源深度学习平台，已被中国企业广泛使用，深度契合企业应用需求，拥有活跃的开发者社区生态。提供丰富的官方支持模型集合，并推出全类型的高性能部署和集成方案供开发者使用。(As an open-source deep learning platform with advanced technology and complete functions, the paddlepaddle has been widely used by Chinese enterprises, which deeply meets the application needs of enterprises and has an active developer community ecology. Provide a rich set of official support models, and launch a full range of high-performance deployment and integration solutions for developers to use.)

说明：  Python是一种计算机程序设计语言。是一种面向对象的动态类型语言，最初被设计用于编写自动化脚本(shell)，随着版本的不断更新和语言新功能的添加，越来越多被用于独立的、大型项目的开发。(Python is a computer programming language. As an object-oriented dynamic typed language, it was originally designed to write automated scripts (shells). With the updating of versions and the addition of new language functions, it is increasingly used in the development of independent, large-scale projects.)

调用sklearn库中的数据集，对其进行训练集和测试集的划分，之后搭建神经网络完成模型的训练

说明：  用于语音分离的python文件，能有效分离两到三个人的混合语音(Python files for voice separation)

python numpy 的一些基本操作和结果展示。。。。。。。(python numpy basic function)

说明：  基于卷积神经网络（CNN）CNN的图片分类训练代码(CNN network classification training)

python3.7实现SGBM算法实现立体匹配计算视差图(Python3.7 implements SGBM algorithm to realize stereo matching and calculate parallax graph)

说明：  使用多层神经网络对芬兰交通流进行预测。程序包括数据清洗、pandas数据可视化、keras建模、预测结果可视化。数据格式为：点ID，年，天数，小时，分钟，秒，百分之一秒，长度（m），车道，方向，车辆类别，速度(km/h)，有缺陷的（0-错误观察，1=错误观察），总时间（技术），间隔（技术），排队（技术）。共16列数据(A multi-layer neural network is used to predict traffic flow in Finland. The program includes data cleaning, pandas data visualization, keras modeling and prediction result visualization. The data format is: point ID, year, days, hours, minutes, seconds, hundredths of a second, length (m), lane, direction, vehicle category, speed (km / h), defective (0-error observation, 1 = wrong observation), total time (Technology), interval (Technology), queuing (Technology). A total of 16 columns of data)

用python实现的SVM回归预测的程序，通过Anaconda实现对机器学习包sklearn的调用。(SVM regression using python to achieve predictable procedures, machine learning package sklearn call by Anaconda.)

图片分类，图像识别，目标检测的resnet50，python实现。