Model Analysis – Deep Learning and Neural Networks with Python and Pytorch p.8




[ad_1]

Welcome to part 8 of the deep learning with Pytorch series. In this tutorial, we’ll be covering how to do analysis of our model, at least at a basic level, along with honing in more on our training loop and code.

Text-based tutorial and sample code: https://pythonprogramming.net/analysis-visualization-deep-learning-neural-network-pytorch/

Linode Cloud GPUs $20 credit: https://linode.com/sentdex

Channel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/join
Discord: https://discord.gg/sentdex
Support the content: https://pythonprogramming.net/support-donate/
Twitter: https://twitter.com/sentdex
Instagram: https://instagram.com/sentdex
Facebook: https://www.facebook.com/pythonprogramming.net/
Twitch: https://www.twitch.tv/sentdex

#pytorch #python #deeplearning

Source


[ad_2]

Comment List

  • sentdex
    November 22, 2020

    A simple way to smooth the accuracy and loss graphs using pandas exp weighted moving avg:

    df['train_acc_mva'] = df['train_acc'].ewm(alpha=.02).mean() # exponential weighted moving average

    df['test_acc_mva'] = df['test_acc'].ewm(alpha=.02).mean()

    df['train_loss_mva'] = df['train_loss'].ewm(alpha=.02).mean()

    df['test_loss_mva'] = df['test_loss'].ewm(alpha=.02).mean()

    Then plot using pandas:
    df.plot(x='batch_ind', y=['train_acc_mva', 'test_acc_mva'], figsize=(8,4))

    plt.ylabel("Accuracy")
    df.plot(x='batch_ind', y=['train_loss_mva', 'test_loss_mva'], figsize=(8,4))

    plt.ylabel("Loss")

  • sentdex
    November 22, 2020

    Man, please continue this series 🙁

  • sentdex
    November 22, 2020

    NOTE: the "if i % 10 == 0" is not only true for every 10th step because our batch size is 100, so it's actually true EVERY STEP. That's why it takes so much longer, what we actually intended to avoid. Instead you could say: "if i % 9 == 0" beacause now it will only calculate it every 10th step! (note that range(0, len(train_X), BATCH_SIZE) will output 0, 100, 200 etc for i, so if i = 900 it's the 10th step)

  • sentdex
    November 22, 2020

    Really great tutorials. So much better than the pytorch docs! Thanks.

  • sentdex
    November 22, 2020

    ROLL TIDE ROLL didn't know you were a BAMA fan!!

  • sentdex
    November 22, 2020

    What is the negative time in the plot? We are plotting time vs acc or loss. Why do we get plot for negative time less than 0??

  • sentdex
    November 22, 2020

    Hello nice job! Would be nice if u continued with this series

  • sentdex
    November 22, 2020

    94 комментария и ни одного на русском

  • sentdex
    November 22, 2020

    Will you make more videos about pytioch?

  • sentdex
    November 22, 2020

    The proposed random is not equally distributed.
    The start and end-range will not be used as often as the middle part wich can be selected both by start as well as by the end.
    For size 2 on a len of 4, both 0 and 3 are used once while 1 and 2 are used twice.
    0 1 2 3:
    XX
    XX
    XX
    1,2,2,1
    For size 3 and len 5, indexes 0 and 4 are only used once, while 2 is used all 3 times.
    0 1 2 3 4:
    XXX
    XXX
    XXX
    1,2,3,2,1
    Then again I understand that the random was not the main part of the video.

  • sentdex
    November 22, 2020

    Thanks man.

  • sentdex
    November 22, 2020

    Does it mean, that if we would train the same model with much bigger data that it would not overfit? Is it possible no mater how long the training takes that a model would not over fit?

  • sentdex
    November 22, 2020

    Your series is amazing ❤ can you do RNN with text generation in PyTorch?

  • sentdex
    November 22, 2020

    Yeah you did the same mistake where you update after each example rather than after each batch. In this code, the additional iteration over the batch is actually pointless.

  • sentdex
    November 22, 2020

    Thanks for the series man! But i think we got one thing missing, how to properly save the model for using it later, or continue with the training after a checkpoint. https://pytorch.org/tutorials/beginner/saving_loading_models.html

  • sentdex
    November 22, 2020

    Hey, I think a proper way to validate over the test set inside of your training loop is to do this once in a while as you otherwise end up taking the most of your time validating over your test set. Also, I don't think validating over a small fraction of your test set is not really valid. You definitely get wrong numbers as the accuracy for one fraction of the test set may be different to another fraction.

  • sentdex
    November 22, 2020

    the best series I have ever known for learning pytorch! But it could be better if some code of photographing the feature map could be added. Anyway, give you a thumb!

  • sentdex
    November 22, 2020

    Bro any idea about stock market chart pattern identification advance thanks

  • sentdex
    November 22, 2020

    How to show a graph in real-time when the model is still training?

  • sentdex
    November 22, 2020

    Best series 🙂 Wanna learn more with pytorch. More series needed!! 💕

  • sentdex
    November 22, 2020

    Can you please make a tutorial on distiller from intel

  • sentdex
    November 22, 2020

    just finished the whole pytorch playlist !! love it thanks @sentdex keep it up 😉

  • sentdex
    November 22, 2020

    please make a video about SSD object detection on pytorch

  • sentdex
    November 22, 2020

    Do you even plan on coming back to do data augmentation for unbalanced datasets or transfer learning?

  • sentdex
    November 22, 2020

    How did you get the command prompt while in sublime?

  • sentdex
    November 22, 2020

    Thank you for putting together this series. I really enjoyed watching it. Are you going to do any more video on pytorch?
    Since you asked for requests, I will: Would love a video digging more in data preparation,including data augmentation. As you mention in your #5, data preparation can be a really tedious task.. would love to hear more about it 😀
    Thanks again.Great job @sentdex

  • sentdex
    November 22, 2020

    Don't spaghet to leave a like on the video people

  • sentdex
    November 22, 2020

    Dude what happened to this series?? 🙁

  • sentdex
    November 22, 2020

    pls continue this series 😀 . i'm waiting for that

  • sentdex
    November 22, 2020

    Thank for the tutorials. but how do i use this model to other pitcher i took , i'm struggle load the image to this model,it error Expected 4-dimensional input for 4-dimensional weight [32, 1, 5, 5], but got input of size [1, 50, 50] instead

  • sentdex
    November 22, 2020

    Thanks dude, that was awesome! 🙂

Write a comment