Lesson 2 - Logistic Regression for Classification

:arrow_forward: Lecture Video will be available on the course page :point_up_2:

Topics Covered:

  • Downloading & processing Kaggle datasets
  • Training a logistic regression model
  • Model evaluation, prediction & persistence

:spiral_notepad: Notebooks used in this lesson:

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:question: Asking/Answering Questions

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for age factor should scaling be consirdered ? if i dont include age in scaling will it affect in accuracy of the model?

I think it should be considered, you can try and see what effect does it have. Maybe it can increase the accuracy of the model.

okay i will thank you very much

Hey @aakashns ,can we have a friendly kaggle competition(like we had for pytorch: zero to Gans) for this course as well?

model.fit(train_inputs[numeric_cols + encoded_cols], train_targets)

i have tried running this block of code and i keep getting this error

ValueError Traceback (most recent call last)
in ()
----> 1 model.fit(train_inputs[numeric_cols + encoded_cols], train_targets)

ValueError: operands could not be broadcast together with shapes (16,) (102,)