Logistic Regression using Python (Sklearn, NumPy, MNIST, Handwriting Recognition, Matplotlib)




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Logistic Regression using Python (Sklearn, NumPy, MNIST, Handwriting Recognition, Matplotlib). This tutorial goes over logistic regression using sklearn on the digits and MNIST datasets including making confusion matrixes.

Logistic Regression Code + Blog Post: https://medium.com/@GalarnykMichael/logistic-regression-using-python-sklearn-numpy-mnist-handwriting-recognition-matplotlib-a6b31e2b166a

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Comment List

  • Michael Galarnyk
    December 26, 2020

    No information about the model parameters itself !

  • Michael Galarnyk
    December 26, 2020

    thanks dude

  • Michael Galarnyk
    December 26, 2020

    I recently created a course called Python for Data Visualization: https://www.linkedin.com/learning/python-for-data-visualization/effectively-present-data-with-python
    for LinkedIn Learning.

  • Michael Galarnyk
    December 26, 2020

    I can't hear you -.-

  • Michael Galarnyk
    December 26, 2020

    brillant work michael

  • Michael Galarnyk
    December 26, 2020

    on loading the training images and labels it gives me Invalid argument
    what should i do??

  • Michael Galarnyk
    December 26, 2020

    Thanks for this helpful tutorial!

    Quick fix regarding future_warning:
    logisticRegr = LogisticRegression(solver = 'liblinear', multi_class = 'ovr')

  • Michael Galarnyk
    December 26, 2020

    May I know why did you use the logistics regression for this type of classification? I got the understanding of the code till the pre-processing of the data set. but the logic behind this prediction is not understandable yet. Please note: I am a beginner.

  • Michael Galarnyk
    December 26, 2020

    i like this video, thank you so much
    and i want to download your unzip mnist data, but t10k-labels-idx1-ubyte this page got error, another things are fine, feedback plz

  • Michael Galarnyk
    December 26, 2020

    Muito bom! Obrigado!

  • Michael Galarnyk
    December 26, 2020

    nice

  • Michael Galarnyk
    December 26, 2020

    Awesome

  • Michael Galarnyk
    December 26, 2020

    Great work…

  • Michael Galarnyk
    December 26, 2020

    Thanks Michael! Keep up the great work!

  • Michael Galarnyk
    December 26, 2020

    Super helpful as always.

  • Michael Galarnyk
    December 26, 2020

    Brilliant!!!

  • Michael Galarnyk
    December 26, 2020

    G8 video as always. I like the way you use Jupyter notebook to the fullest. I'm learning machine learning nowadays and this tutorial definitely cleared my concept on linear regression.

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