Python-Machine-Learning
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dlab-berkeley
D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn in Python.
in the tree visualization, we are using the wrong dataset so it's only classifying 2 types of penguins and not all three that we have in the data
Doing normalization without dropping NaN values should return an error in the challenge but it doesn't
This pull request is to fix a bug that occurs due to a change in the Pandas library interface. The interface of pd.DataFrame.dropna() changed. The argument `subset` no longer accepts...
When using Pandas version > 2, the correlation code requires an additional argument. Running data.corr() might give an error which looks like this: ValueError: could not convert string to float:...
Here is some feedback for the workshop and I'd love to participate in improving the workshop! Presenter: - Excellent pacing and very clear explanation of complex concepts! - Multiple breaks...
We received a lot of questions about fit_transform and transform Having a dedicated section briefly explaining fit vs fit_transform vs transform (or link to a document/article) might be helpful for...
The solution for the lesson 3 is missing codes and should be updated with codes (for challenge 2 and maybe for 3)
Version issues: Some participants have issues with: data = data.dropna(subset='sex') Fixed by using: data = data.dropna(subset=['sex'])
Is there a link to the slides used in the regression lesson (not the introduction slides)?
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D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn in Python.