Book Image

Streamlit for Data Science - Second Edition

By : Tyler Richards
3.3 (3)
Book Image

Streamlit for Data Science - Second Edition

3.3 (3)
By: Tyler Richards

Overview of this book

If you work with data in Python and are looking to create data apps that showcase ML models and make beautiful interactive visualizations, then this is the ideal book for you. Streamlit for Data Science, Second Edition, shows you how to create and deploy data apps quickly, all within Python. This helps you create prototypes in hours instead of days! Written by a prolific Streamlit user and senior data scientist at Snowflake, this fully updated second edition builds on the practical nature of the previous edition with exciting updates, including connecting Streamlit to data warehouses like Snowflake, integrating Hugging Face and OpenAI models into your apps, and connecting and building apps on top of Streamlit databases. Plus, there is a totally updated code repository on GitHub to help you practice your newfound skills. You'll start your journey with the fundamentals of Streamlit and gradually build on this foundation by working with machine learning models and producing high-quality interactive apps. The practical examples of both personal data projects and work-related data-focused web applications will help you get to grips with more challenging topics such as Streamlit Components, beautifying your apps, and quick deployment. By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly.
Table of Contents (15 chapters)
13
Other Books You May Enjoy
14
Index

Improving job applications in Streamlit

Often, data science and machine learning job applications rely on take-home data science challenges to judge candidates. Frankly, this is a brutal and annoying experience that companies can demand because of the dynamic between the applicant and the employer. For instance, it could take a candidate 5–10 hours to fully complete a data science challenge, but it might only take the employer 10 minutes to evaluate it. Additionally, an individual virtual or telephone interview might take 30–45 minutes for the employer, plus an extra 15 minutes to write up feedback, compared to the same 30–45 minutes for the applicant. Because getting 5–10 hours of work gives them a very high signal per minute of employee time, employers have trended toward including these challenges within their job applications.

You can use the opportunity here to use Streamlit to stand out from the crowd by creating a fully functioning application...