Classify Images Using Python & Machine Learning




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Classify Images Using Machine Learning & Convolutional Neural Networks (CNN)

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#MachineLearning #CNN #Python #ImageClassifiaction

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Comment List

  • Computer Science
    December 25, 2020

    Heeeeelp me i have a question?

  • Computer Science
    December 25, 2020

    where is test and train data set and how it is returning index to you

  • Computer Science
    December 25, 2020

    How can u extract the label of a classified image? I would like to classify food and recommend recipes based on the label identified but I am not understanding how to do this. I WOULD kindly ask a tutorial on this matter. There is barely information on food related projects plz

  • Computer Science
    December 25, 2020

    hi sir why do we need to resize? is 32 32 3 standard size?

  • Computer Science
    December 25, 2020

    thank you very much sir for this video

  • Computer Science
    December 25, 2020

    07:00 shape data

  • Computer Science
    December 25, 2020

    I got a syntax Error
    When adding the flattering layer with syntax

    model.add(Flatten())

    How to overcome this?

  • Computer Science
    December 25, 2020

    in which platform you did write the code?

  • Computer Science
    December 25, 2020

    Could you please elaborate more about the model, why did you take (5,5) in first conv2d layer and is 32 number of neurons? And can we choose any max pooling value?

  • Computer Science
    December 25, 2020

    I m getting error as" import error at sequential",
    I installed pip install sequential also, still having this problem
    pls help me

  • Computer Science
    December 25, 2020

    NOTE:
    Following packages which are very essential for CNN (Convolutional Neural Networks) are reorganized into different packages

    from keras.layers.convolutional import Conv2D

    from keras.layers import Dense

    from keras.layers.convolutional import MaxPooling2D

    from keras.layers import Flatten

  • Computer Science
    December 25, 2020

    thanks a lot for the fruitful video…can I use it for my model purposes …thanks in advance

  • Computer Science
    December 25, 2020

    Hi ! Thanks a lot for the video !
    I still have a problem :
    Epochs are only outputting over 93 images whereas i have something like 1029 images.
    (my model.fit is set with batch_size=10 and validation_split=0.1)
    As a result, each val_accuracy, loss … are the same for each epoch

    Any idea ? Thank you again

  • Computer Science
    December 25, 2020

    helllo there,i have written the code as it is,but while training the model it is training for 157/157 for each epoch where as in ur case it is for 40,000 samples what can be the reason?Can u help me sir

  • Computer Science
    December 25, 2020

    Awesome!! TQVM.

  • Computer Science
    December 25, 2020

    Thanks alot for video.
    I have few queries,
    How to get classification done automatically from data.
    ?
    In tutorial, you know already the sequence.

  • Computer Science
    December 25, 2020

    Bro can you predict the pubg zones using
    Deep learning…..

  • Computer Science
    December 25, 2020

    great , thanks

  • Computer Science
    December 25, 2020

    thanks a lot. it works properly.

  • Computer Science
    December 25, 2020

    Can I use it on own dataset?

  • Computer Science
    December 25, 2020

    good tutorial ive found that i keep getting model must be compiled before running but ive followed all the same steps is there a way to fix this thanks in advance

  • Computer Science
    December 25, 2020

    can i use this way for x-ray detection???

  • Computer Science
    December 25, 2020

    Thanks for this wonderful video. Really a good learning from this.

  • Computer Science
    December 25, 2020

    Just FYI… code @ 37.18 can be rewritten as below.. which is much easier. If like to do so 🙂
    This will also result the same. It just we do not need to have list_index and loop over it. But yes to undersnatd the logic thats the best thing. The below is just a short way to get the result.
    `
    classification[np.argmax(predictions)]
    `

  • Computer Science
    December 25, 2020

    Hello im from Indonesia, i wanna ask about different case sir ? so In my case my own datasets in google drive not like in tutorial so do you can help me what should I do for make my Data Training as x_train and my validation as y_test

  • Computer Science
    December 25, 2020

    Tq for u r video

  • Computer Science
    December 25, 2020

    Is it possible to grab url google images on a specific thing instead of just one image?

  • Computer Science
    December 25, 2020

    How would you train it for higher accuracy? I’m assuming repeating train steps above? Also when you add (dog, cat, etc.) would i be able to add as many as i want to get the model to train on more things?

  • Computer Science
    December 25, 2020

    well done!

  • Computer Science
    December 25, 2020

    do you have a tutorial for how to download tensorflow with pip, it doesn't work for me and i wnat to download it

  • Computer Science
    December 25, 2020

    It would be great if you could explain why are you adding all those layers, otherwise it looks like you are just throwing layers for the luls. Also it would be amazing if you could explain why are you using those numbers at the layers
    example: model.add(Dense(500, activation='relu')) Why 500 neurons? Why not 400? Why relu?
    Another example from your guide: "Create one more convolution layer and pooling layer like before, but without the input_shape > model.add(Conv2D(64, (5, 5), activation='relu')) " Why are you creating one more convolution layer? Why are you adding a pooling layer?.. And so on. It would improve the understanding of what we are doing 🙂

    Thanks for a great guide!

  • Computer Science
    December 25, 2020

    I'm getting the error " NameError: name 'MaxPooling2D' is not defined.
    I double-checked to make sure I imported everything correctly. And my code is exactly as follows. All the previous cells have worked so far.

  • Computer Science
    December 25, 2020

    Great video, thank you

  • Computer Science
    December 25, 2020

    hey CS first of call I want to say thanks for the video and I'm having trouble seeing the images pop up when i run it.

  • Computer Science
    December 25, 2020

    Cool – this is the shortest route to successfully pogramming digit recognition I have seen so far! Keep it up! I am looking forward to seeing more ANN/ML examples on this channel. BTW It would be great if you posted a link to the code.

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