How to Build a Machine Learning Hyperparameter Optimization App | Streamlit #14

In this video, I will be showing you how to build The Machine Learning App (with Hyperparameter Optimization) in Python using the Streamlit and Scikit-learn library. This web app will allow users to upload their own CSV file and the web app will automatically build random forest models by performing a grid hyperparameter search.

👉 Code: https://github.com/dataprofessor/ml-o...
👉 Demo: https://share.streamlit.io/dataprofes...

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Check out our other videos in the following playlists.
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✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-p...
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✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit
✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny
✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-c...
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✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds
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✅ Weka (No Code Machine Learning): http://bit.ly/dp-weka

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✅ Data Science from Scratch : https://amzn.to/3fO0JiZ
✅ Python Data Science Handbook : https://amzn.to/37Tvf8n
✅ R for Data Science : https://amzn.to/2YCPcgW
✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv
✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd

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