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Furkan M. Torun - Become a Data Storyteller with Streamlit! [PyData Prague 2023-11-20]
Become a data storyteller with Streamlit, an open-source tool for rapid prototyping and deployment of machine learning models. Learn how to create interactive web applications, integrate with popular libraries, and deploy models to a public-facing URL.
- Streamlit is an open-source tool for rapid prototyping and deployment of machine learning models.
- It’s a lightweight and flexible tool that can be used to create interactive web applications.
- Streamlit allows for easy integration with Python visualization libraries, such as Plotly and Seaborn.
- It also allows for user interactivity, which enables users to interact with the model and change parameters in real-time.
- Streamlit is compatible with the entire Python data science ecosystem, including popular libraries such as Pandas, NumPy, and Matplotlib.
- It’s also possible to deploy Streamlit apps on a public-facing URL, making it easy to share and collaborate with others.
- Streamlit offers a built-in chat component and support for multiple pages, making it suitable for complex applications.
- It’s fast and easy to use, with minimal overhead and no need to write front-end code.
- Streamlit can be used for data storytelling, allowing users to explore and visualize data in a interactive and engaging way.
- It’s also possible to use Streamlit for model deployment, making it a useful tool for data scientists and engineers.
- Streamlit is highly compatible with other popular machine learning and visualization libraries, such as TensorFlow, Keras, and scikit-learn.
- It’s available for free and open-source, with active community support and a growing list of tutorials and resources.
- Streamlit’s ease of use and flexibility make it an ideal tool for rapid prototyping and deploying machine learning models.