搜索资源列表
mnist实验
- 包含训练用的图片数据包，python源代码，mnist实验，深度学习，进行图片分类(mnist experiment.python code.deep learning.picture classification,etc.)
solving_captchas_code_examples
- 对网站验证图片进行分类识别，基于python语言，采取机器学习方式(Website verification images for classification and identification)
bayes
- 自己书写的一段机器学习的朴素贝叶斯算法，基于Python实现(The Implementation of Bayes Algorithm in Python)
[Peter_Harrington]_Machine_Learning_in_Action
- 机器学习入门书籍，结合python,适合初学者来阅读。(The machine learning based on the python is suitable to the freshman.)
DeepLearning
- DeepLearning 工具包C, C++, Java, phython, scala代码集合,(DeepLearning Toolkit :C, C ++, Java, phython, scala code collection)
deep_ocr-master
- ocr,一个深度学习的ocr开源代码，非常不错的ocr。(ocr, this is a great ocr open source code by Python. Very nice project.)
程序
- python 鱼C论坛零基础入门学习python(Python fish C forum zero base introduction to learning Python)
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)
简单PSO
- PSO小程序，能优化机器学习等方法的参数，利用python平台实现，具有很好的实用性(PSO small program can optimize the parameters of machine learning and other methods. It is realized with the python platform. It has good practicability.)
face
- 系统介绍：基于树莓派官方系统stretch 系统，系统内安装了opencv3.3.0以及 tensorflow1.1.0 。人脸识别门禁的代码在里面目录/home/pi/face。内安装了深度学习的案例。 程序启动说明：开机前连接树莓派摄像头或网络USB摄像头，网络摄像头无需下面的设置。如使用树莓派摄像头则在终端输入 sudo nano /etc/modules-load.d/modules.conf 在最后添加一行添加
jfinal-3.3_demo
- JFinal 是基于 Java 语言的极速 WEB + ORM 框架，其核心设计目标是开发迅速、代码量少、学习简单、功能强大、轻量级、易扩展、Restful。在拥有Java语言所有优势的同时再拥有ruby、python、php等动态语言的开发效率！为您节约更多时间，去陪恋人、家人和朋友 :)(JFinal is a fast WEB + ORM fr a mework based on Java language. Its core d
Machine Learning in Java
- 这是一本全英文的关于机器学习技术书，与当今市面上大多数使用python进行机器学实现的书不同，本书讲解的是基于Java语言的机器学习的学习与代码实现。(MachineLearning implemented with Java)
单层感知器
- 基于深度学习实现单层感知器的python代码，用单层感知器处理非线性分类问题,观察结果。(The Python code of single layer perceptron is realized based on depth learning, and the nonlinear classification problem is processed with a single layer perceptron, and the r
TensorVision
- tensorvision的库文件，用于python机器学习的编程(The library file of tensorvision is used for Python machine learning programming.)
opencvpython
- 图像处理python表代码。其中有一部分是基于深度学习的。(Image processing Python table code. Some of them are based on deep learning.)
unet
- unet网络的python版本,一种非常成功的图像学习模型，用于生物医学图像分割(a unet model wrote by python)
kNN
- 机器学习/python入门项目一：聚类kNN(Machine learning / python entry project: clustering kNN)
decision_tree
- 机器学习/python入门项目三：决策树(Machine Learning / Python Getting Started Project 3: Decision Trees)
kmeans
- 机器学习/python入门项目五：k均值(Machine learning / python entry project five: k means)
qlearning4k-master
- qlearning4k是强化学习Python深度学习lib库Keras插件。它简单，是快速成型的理想选择。(Qlearning4k is a reinforcement learning add-on for the python deep learning library Keras. Its simple, and is ideal for rapid prototyping.)