Machine Learning Model Deployment Using Streamlit

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In this video, we focus on deploying our model as API using the streamlit library. This way, the solution can be consumed via API.

Learn how to build a Machine learning model and deploy the solution.
From idea generation to execution. making what seems to be complex for Data Science Enthusiasts easy. A lot of people take courses and still end up with a knowledge gap.

I have been there before and in this FREE course, we will give you your Ah-mazing moment!

#modeldeployment #streamlit #machinelearning
  1. TheOyinbooke
  2. datascience
  3. data science
  4. machine learning
  5. model deployment using flask
  6. how to
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Комментарии
Автор

Thanks.really helpful. Please how do I use tabs in streamlit

simisolaolagunju
Автор

Hi, Olanrewaju. I've been watching your videos and you have amazing work on your profile. I've tried to follow your videos and I've managed to write up a code to use. I used the streamlit method but I keep getting an error from the software that the xgboost is not installed and even when I use the pip install xgboost I am still getting that error. Would it be possible for me to send you my code and pkl file so you can run it for me on your PC ? thanks a lot

Kevin-gzth
Автор

Thank you so much for this video, please I need help. Each time i run my streamlit and click on the Predict button, I experience this error message:
ValueError: dtype='numeric' is not compatible with arrays of bytes/strings.Convert your data to numeric values explicitly instead.


Please i need help, i can share my entire code if you want to.

philipokposoytc