a simple machine learning system demo, for ML study.
Machine Learning System
introduction
This project is a full stack Django/React/Redux app that uses token based authentication with Knox.
Then I add Machine Learning features for demostrate the full workflow of the data mining, including the four stage corresponding to four pages:
- data management
- data explore
- model train
- prediction
The data set is the classic iris data, which is only for demo, and this project is from my interest. so you can reference, but the quality is not assured.
features
- authentication functions
login from login page register your account logout from inner page
- data management
input iris items edit iris items delete iris items
- data explore
inspect attribute distribution through histogram inspect sepal distribution through scatter graph inspect petal distribution through scatter graph
- model train
input cluster number train a cluster model using sklearn-kmeans library inspect cluster result through sepal and petal scatter
- prediction
input iris sepal and petal attributes predict iris cluster
technology stack
| category | name | comment |
|---|---|---|
| frontend | reactjs | frontend framework |
| frontend | redux | state management |
| frontend | react-C3JS | D3 based graph tool |
| frontend | react-bootstrap | style component library |
| frontend | data-ui | react data visualization tool |
| backend | django | backend framework |
| backend | django-rest-knox | authentication library |
| backend | djangorestframework | restful framework |
| backend | sklearn | machine learning tool |
Quick Start
# Install dependencies
cd ./frontend
npm install # Build for production
npm run build # Install dependencies
cd ../backend
pipenv install # Serve API on localhost:8000
pipenv run python manage.py runserver
snapshot
login page

model train page

prediction page

a simple machine learning system demo, for ML study.的更多相关文章
- Stanford机器学习笔记-7. Machine Learning System Design
7 Machine Learning System Design Content 7 Machine Learning System Design 7.1 Prioritizing What to W ...
- Lessons learned developing a practical large scale machine learning system
原文:http://googleresearch.blogspot.jp/2010/04/lessons-learned-developing-practical.html Lessons learn ...
- Machine Learning - 第6周(Advice for Applying Machine Learning、Machine Learning System Design)
In Week 6, you will be learning about systematically improving your learning algorithm. The videos f ...
- Machine Learning - XI. Machine Learning System Design机器学习系统的设计(Week 6)
http://blog.csdn.net/pipisorry/article/details/44119187 机器学习Machine Learning - Andrew NG courses学习笔记 ...
- 【原】Coursera—Andrew Ng机器学习—课程笔记 Lecture 11—Machine Learning System Design 机器学习系统设计
Lecture 11—Machine Learning System Design 11.1 垃圾邮件分类 本章中用一个实际例子: 垃圾邮件Spam的分类 来描述机器学习系统设计方法.首先来看两封邮件 ...
- (原创)Stanford Machine Learning (by Andrew NG) --- (week 6) Advice for Applying Machine Learning & Machine Learning System Design
(1) Advice for applying machine learning Deciding what to try next 现在我们已学习了线性回归.逻辑回归.神经网络等机器学习算法,接下来 ...
- Coursera 机器学习 第6章(下) Machine Learning System Design 学习笔记
Machine Learning System Design下面会讨论机器学习系统的设计.分析在设计复杂机器学习系统时将会遇到的主要问题,给出如何巧妙构造一个复杂的机器学习系统的建议.6.4 Buil ...
- 斯坦福第十一课:机器学习系统的设计(Machine Learning System Design)
11.1 首先要做什么 11.2 误差分析 11.3 类偏斜的误差度量 11.4 查全率和查准率之间的权衡 11.5 机器学习的数据 11.1 首先要做什么 在接下来的视频中,我将谈到机器 ...
- 斯坦福大学公开课机器学习:machine learning system design | data for machine learning(数据量很大时,学习算法表现比较好的原理)
下图为四种不同算法应用在不同大小数据量时的表现,可以看出,随着数据量的增大,算法的表现趋于接近.即不管多么糟糕的算法,数据量非常大的时候,算法表现也可以很好. 数据量很大时,学习算法表现比较好的原理: ...
随机推荐
- python测试开发django-67.templates模板变量取值
前言 django 的模板里面变量取值是通过句点语法来取值,就是一个点(.)符号.取值的对象也可以是字符串,int类型,list列表,字典键值对,也可以是一个类的实例对象. views视图 比如我在 ...
- initState 必须调用 super.initState(); 否则报错
@override void initState() { // initState 必须调用 super.initState(); 否则报错:info: This method overrides a ...
- SpringBoot——探究HelloWorld【三】
前言 前面我们写了helloworld的一个,这里我们对他进行分析 探究 那么下面就开始我们的探究之旅吧,首先从POM文件来,在POM文件中我们导入了项目所需要的依赖 POM文件 父项目 <pa ...
- new的模拟实现
new 一句话介绍 new: new 运算符创建一个用户定义的对象类型的实例或具有构造函数的内置对象类型之一 也许有点难懂,我们在模拟 new 之前,先看看 new 实现了哪些功能. 举个例子: // ...
- WHAT IS THE DIFFERENCE BETWEEN REACT.JS AND REACT NATIVE?
Amit Ashwini - 09 SEPTEMBER 2017 React.js was developed by Facebook to address its need for a dynami ...
- LeetCode 490. The Maze
原题链接在这里:https://leetcode.com/problems/the-maze/ 题目: There is a ball in a maze with empty spaces and ...
- FFT代码详解
关于FFT原理部分的介绍,在网上已经有很多了,所以在此只讲代码实现部分的内容. 原理可以参考https://www.cnblogs.com/RabbitHu/p/FFT.html 推荐看完它的原理解释 ...
- 小程序&app 注册登录、绑定
前段时间开发中的一款产品,有小程序和app:小程序直接微信登录,app使用手机号+验证码注册,手机号+验证码/密码登录. 用户使用其中一套账号密码即可正常使用,不强制要求完善另一套账号.为避免同一用户 ...
- Django 基础篇(二)视图与模板
视图 在django中,视图对WEB请求进行回应 视图接收reqeust对象作为第一个参数,包含了请求的信息 视图就是一个Python函数,被定义在views.py中 #coding:utf- fro ...
- luogu 2742 二维凸包
链接 luogu 模板一 上下利用斜率求凸包然后合并. #include <bits/stdc++.h> using namespace std; const int N=10005; c ...