Welcome to this hands-on project on building your first machine learning web app with the Streamlit library in Python. By the end of this project, you are going to be comfortable with using Python and Streamlit to build beautiful and interactive ML web apps with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 100 lines of Python code! Our web application will allows users to choose what classification algorithm they want to use and let them interactively set hyper-parameter values, all without them knowing to code!

Build a Machine Learning Web App with Streamlit and Python

位教师:Snehan Kekre
访问权限由 New York State Department of Labor 提供
15,784 人已注册
您将学到什么
Build interactive web applications with Streamlit and Python
Train Logistic Regression, Random Forest, and Support Vector Classifiers using scikit-learn
Plot evaluation metrics for binary classification algorithms
您将练习的技能
- Data Visualization Software
- Interactive Data Visualization
- Logistic Regression
- Data Science
- Web Applications
- Machine Learning
- Dashboard
- Model Evaluation
- Pandas (Python Package)
- Predictive Modeling
- Plot (Graphics)
- Python Programming
- Scikit Learn (Machine Learning Library)
- Machine Learning Algorithms
- Data Visualization
- Classification Algorithms
- 技能部分已折叠。显示 9 项技能,共 16 项。
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在 2 小时内学习、练习并应用岗位必备技能
- 接受行业专家的培训
- 获得解决实训工作任务的实践经验
- 使用最新的工具和技术来建立信心

关于此指导项目
分步进行学习
在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:
-
Project Overview and Demo
-
Turn Simple Python Scripts into Web Apps
-
Load the Mushrooms Data Set
-
Creating Training and Test Sets
-
Plot Evaluation Metrics
-
Training a Support Vector Classifier
-
Training a Support Vector Classifier (Part 2)
-
Train a Logistic Regression Classifier
-
Training a Random Forest Classifier
推荐体验
You must understand Logistic Regression, Support Vector Machines, and Random Forest Classifiers and how to use them as scikit-learn estimators
5个项目图片
位教师

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学习方式
基于技能的实践学习
通过完成与工作相关的任务来练习新技能。
专家指导
使用独特的并排界面,按照预先录制的专家视频操作。
无需下载或安装
在预配置的云工作空间中访问所需的工具和资源。
仅在台式计算机上可用
此指导项目专为具有可靠互联网连接的笔记本电脑或台式计算机而设计,而不是移动设备。
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学生评论
- 5 stars
73.31%
- 4 stars
22.11%
- 3 stars
3.60%
- 2 stars
0.24%
- 1 star
0.72%
显示 3/416 个
已于 Nov 3, 2021审阅
Excellent course for those who have machine learning knowledge and want to deploy ML model as the web app.
已于 Aug 16, 2020审阅
Very good guided course. I learned how to create a Web App without much coding for my ML projects. Thanks for explaining everything in so easy way.
已于 May 20, 2020审阅
The Course was Really Nice.The Reading Material was Good Enough to Understand.All the Videos Explained the Concepts Nicely.I Really Appreciate This Course.






