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所在平台: Udemy |
课程主页: https://www.udemy.com/course/streamlit-for-datascience/
课程评论：没有评论
**课程概述：** 本课程旨在教授学员如何使用 Streamlit 这个开源 Python 库来创建和部署数据科学 Web 应用。Streamlit 能够帮助您快速构建美观、可定制的 Web 应用，用于展示分析结果、构建交互式体验以及演示机器学习模型。课程时长短，开发部署高效，能将应用开发时间从几天缩短到几小时。 **课程内容：** * **Streamlit 基础：** 了解 Streamlit 的优势，学习安装 Streamlit，如何运行和编辑演示应用，以及如何组织 Streamlit 项目。 * **创建自己的 Streamlit 应用：** 从零开始构建属于自己的 Streamlit 应用。 * **数据可视化：** 学习在 Streamlit 中进行数据可视化，包括接受用户输入并为应用添加文本元素。 * **集成交互式组件：** 将 Streamlit 的各种组件（widgets）与可视化结合，提升用户体验。 * **第三方可视化库集成：** 学习如何集成 Plotly 和 Bokeh 等可视化库。 * **端到端项目：** 完成一个数据科学项目，并将部署数据科学 Web 应用到云端。 **课程目标：** 完成本课程后，学员将能够独立开始创建自己的 Streamlit 数据科学 Web 应用。
Welcome to the course Learn Streamlit for Data ScienceStreamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science that can be used to share analytics results, build complex interactive experiences, and illustrate new machine learning models. In just a few minutes you can build and deploy powerful data apps. On top of that, developing and deploying Streamlit apps is incredibly fast and flexible, often turning application development time from days into hours. In this course, we start out with the Streamlit basics. We will learn how to download and run demo Streamlit apps, how to edit demo apps using our own text editor, how to organize our Streamlit apps, and finally, how to make our very own. Then, we will explore the basics of data visualization in Streamlit. We will learn how to accept some initial user input, and then add some finishing touches to our own apps with text. At the end of this course, you should be comfortable starting to make your own Streamlit applications.In particular, we will cover the following topics: Why Streamlit? Installing Streamlit Organizing Streamlit apps StreamlitText ElementsDisplay DataLayoutsWidgetsData VisualizationIntegrating Widgets to VisualizationsPlotlyBokehStreamlitData Science Project Deploy Data Science Web App in Cloud
