it wass very helpful i got a suggestion do look into it instead of we giving all the parameters, let the user select the model and the associated parameters create a drop down with all models and when a user select a model then the user can define parameter value for the selected model for eg kfold, seeds value etc...
Hi Jessie, thank you for making these videos. Do you have any video on how to build dashboards with streamlit with proper layout on the webpage? Merry Christmas and good year ahead.
Hey hi! I am getting an bug like the whole content is getting collapsed, when i use file uploader inside a select box condition. I am getting output when i m using normal way to read file, i m getting output. Can you give a solution? Thank u
that's a great work dear brother.. Very helpful stuff and can you give me some idea how the data processing is done there? like missing value imputation, outlier dealing etc.. thank you
Hi Dubasi, pls this is just a simple app and the datasets used were mostly cleaned and well prepared before uploading to give the expected result. But you can add more features to make it more robust. Hope it helps
hii Your videos are so informative . I need a help using Streamlit.. I have a table where i did to make column values clickable. IF we click on the column value a POP-up with detailed report needs to generated. Pls help me. It would be grateful. Thanks
Hi Jessie, I tried to follow your tutorials and got stuck at the Model Building for name, model in models: kfold = model_selection.KFold(n_splits=10, random_state=seed, shuffle=True) cv_results = model_selection.cross_val_score(model, X, y, cv=kfold, scoring=scoring)# kfold model_names.append(name) model_mean.append(cv_results.mean()) model_std.append(cv_results.std()) I get following error message: TypeError: Cannot clone object. You should provide an instance of scikit-learn estimator instead of a class. Traceback: File "C:\Users\asdf\Streamlit_APP_ML\main.py", line 144, in main cv_results = model_selection.cross_val_score(model, X, y, cv=kfold, scoring=scoring) Do you have any idea what might be my mistake?
it wass very helpful
i got a suggestion do look into it
instead of we giving all the parameters, let the user select the model and the associated parameters
create a drop down with all models and when a user select a model then the user can define parameter value for the selected model for eg kfold, seeds value etc...
Excellent Suggestion Kumar
I have a lot of confusion on drags and drop..this video is awesome...lots of thanks..
Glad it was helpful!
Can we take dataframe as input as make batch predictions?
When he says "Very Interesting" , i smile
Lol Manish. haha
Hi Jessie, thank you for making these videos. Do you have any video on how to build dashboards with streamlit with proper layout on the webpage?
Merry Christmas and good year ahead.
Merry Christmas Deepak, will be looking into it. Thanks for that suggestion.
Hey hi! I am getting an bug like the whole content is getting collapsed, when i use file uploader inside a select box condition. I am getting output when i m using normal way to read file, i m getting output. Can you give a solution? Thank u
that's a great work dear brother..
Very helpful stuff and can you give me some idea how the data processing is done there? like missing value imputation, outlier dealing etc..
thank you
Hi Dubasi, pls this is just a simple app and the datasets used were mostly cleaned and well prepared before uploading to give the expected result. But you can add more features to make it more robust. Hope it helps
@@JCharisTech thank you brother.. it helps me a lot
hii Your videos are so informative . I need a help using Streamlit.. I have a table where i did to make column values clickable. IF we click on the column value a POP-up with detailed report needs to generated. Pls help me. It would be grateful.
Thanks
Hi Anu, for this we can try using the custom component or a different approach using html and js. Will have to look into this. Thanks, Glad this helps
Well explained. Thanks a lot Jessie!!
Glad it was helpful!
This is great, thanks JCharis!
Thanks TC Ricks, glad it was helpful
Happy Holidays
Hi Jessie, I tried to follow your tutorials and got stuck at the Model Building
for name, model in models:
kfold = model_selection.KFold(n_splits=10, random_state=seed, shuffle=True)
cv_results = model_selection.cross_val_score(model, X, y, cv=kfold, scoring=scoring)# kfold
model_names.append(name)
model_mean.append(cv_results.mean())
model_std.append(cv_results.std())
I get following error message:
TypeError: Cannot clone object. You should provide an instance of scikit-learn estimator instead of a class.
Traceback:
File "C:\Users\asdf\Streamlit_APP_ML\main.py", line 144, in main
cv_results = model_selection.cross_val_score(model, X, y, cv=kfold, scoring=scoring)
Do you have any idea what might be my mistake?
Hello Binayak, the ML estimators eg LogisticRegression, etc needs to be initialized as `LogisticRegression()`
Hope this helps
Thank you Jessie
Glad it helped Bosun
Very good tutorial and well-explained. Thank you
Thanks a lot Jeff,Merry Christmas
Hey can you please do a tutorial on Image classification using Streamlit and Python.
...
Thanks for this tutorial
WOW
@JCharisTech copyright!!