Build a Machine Learning Web App with Streamlit and Python
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
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! Prior experience with writing simple Python scripts and using pandas for data manipulation is recommended. It is required that you have an understanding of Logistic Regression, Support Vector Machines, and Random Forest Classifiers and how to use them in scikit-learn. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
您要培养的技能
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
指导项目工作原理
您的工作空间就是浏览器中的云桌面，无需下载
在分屏视频中，您的授课教师会为您提供分步指导
审阅
来自BUILD A MACHINE LEARNING WEB APP WITH STREAMLIT AND PYTHON的热门评论
The Course was Really Nice. The Reading Material was Good Enough to Understand.\n\nAll the Videos Explained the Concepts Nicely.\n\nI Really Appreciate This Course.
Use of evaluation metrics and plotting looks good, but if used plotting function (scatter plot of x-test and y-test) can be easy to view and understand the plot
Excellent project.Top class stuff from the instructor to make the learning fun and explain a beautiful piece of technology in a simple and efficient way.
A great introductory guided project that fueled my enthusiasm for data science and machine learning with knowledge and practical skills.
常见问题
常见问题
如果我购买指导项目，会得到什么？
购买指导项目后，您将获得完成指导项目所需的一切，包括通过 Web 浏览器访问云桌面工作空间，工作空间中包含您需要了解的文件和软件，以及特定领域的专家提供的分步视频说明。
指导项目可在台式设备和移动设备上学习吗？
由于您的工作空间包含适合笔记本电脑或台式计算机使用的云桌面，因此指导项目不在移动设备上提供。
指导项目的讲师是谁？
指导项目讲师是特定领域的专家，他们在项目的技能、工具或领域方面经验丰富，并且热衷于分享自己的知识以影响全球数百万的学生。
我能在完成指导项目后从中下载作品吗？
您可以从指导项目中下载并保留您创建的任何文件。为此，您可以在访问云桌面时使用‘文件浏览器’功能。
我能够退款吗？退款政策是如何规定的？
指导项目不符合退款条件。请查看我们完整的退款政策。
有助学金吗？
指导项目不提供助学金。
我能旁听指导项目并免费观看视频部分吗？
指导项目不支持旁听。
我需要具备多少经验才能做这个指导项目？
您可在页面顶部点按此指导项目的经验级别，查看任何知识先决条件。对于指导项目的每个级别，您的讲师会逐步为您提供指导。
我能直接通过 Web 浏览器来完成此指导项目，而不必安装特殊软件吗？
是，您可以在浏览器的云桌面中获得完成指导项目所需的一切。
指导项目的学习体验如何？
您可以直接在浏览器中于分屏环境下完成任务，以此从做中学。在屏幕的左侧，您将在工作空间中完成任务。在屏幕的右侧，您将看到有讲师逐步指导您完成项目。
还有其他问题吗？请访问 学生帮助中心。
