# My Very First Streamlit app

**URL:** <https://discuss.streamlit.io/t/my-very-first-streamlit-app/20429>\
**Category:** Show the Community!\
**Created:** [December 29, 2021, 1:01am UTC](https://discuss.streamlit.io/t/my-very-first-streamlit-app/20429 "2021-12-29T01:01:57Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![KinePi](https://sea2.discourse-cdn.com/streamlit/user_avatar/discuss.streamlit.io/kinepi/32/15023_2.png) [@KinePi](https://discuss.streamlit.io/u/KinePi)\
**Post date:** [December 29, 2021, 1:01am UTC](https://discuss.streamlit.io/t/my-very-first-streamlit-app/20429/1 "2021-12-29T01:01:57Z")

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![Streamlit](https://global.discourse-cdn.com/streamlit/original/2X/c/cf024fe234f1646a730fb1ff7216b144a2914277.png)  
In this data science project, I developed a credit card fraud detection model, and this web interface was used to walk through the project from dataset balancing to model development. Three of the five models utilized in the development of the model were employed in this web app. [Decision Tree Classifier], [Random Forest Classifier], and [Extreme Gradient Boosting] are the three algorithms. On GitHub, you can get the source code for Streamlit CFDM app: [https://github.com/kinematic2002/Streamlit](https://github.com/kinematic2002/Streamlit) CFDM app

Take a look!!  
[https://share.streamlit.io/kinematic2002/streamlit\_cfdm\_app/main/main\_streamlit.py](https://share.streamlit.io/kinematic2002/streamlit_cfdm_app/main/main_streamlit.py)

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**Author:** ![system](https://global.discourse-cdn.com/streamlit/original/3X/c/f/cf4c2ee0d938358f82448c5fe4b9c3c91d7ce19c.svg) [@system](https://discuss.streamlit.io/u/system)\
**Post date:** [December 29, 2022, 1:02am UTC](https://discuss.streamlit.io/t/my-very-first-streamlit-app/20429/2 "2022-12-29T01:02:28Z")

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