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Week 4 - Convolutional Neural Networks, Part I

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This week you will...

  • go deeper into using ConvNets with real-world data and a much larger dataset than those you've been using thus far.

  • learn about image augmentation, a technique to avoid overfitting by tweaking the training set to potentially increase the diversity of subjects it covers.

  • discuss your project ideas.

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Slides

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Learning Resources

  • (StatQuest with Josh Starmer, 15 min)

  • (DeepLearningAI, 9:50 min)

  • (DeepLearningAI, 9:30 min)

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Until next week you should...

  • watch video to get an introduction on transfer learning (8 min)

  • watch video to learn how to implement transfer learning with CNNs (12 min)

  • work through blog to learn about multi-class classification

(Aladdin Persson, first 10 min)
  • (Aladdin Persson, first 7 min)

  • (Kody Simpson, 23 min)

  • complete the exercise assignment in
  • investigate the characteristics of your project's dataset according to the instructions given

  • document your findings on the dataset characteristics according to the instructions of above

  • file-pdf
    627KB
    251113_CNN_Part_I.pdf
    PDF
    arrow-up-right-from-squareOpen
    Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs) arrow-up-right
    C4W1L04 Paddingarrow-up-right
    C4W2L10 Data Augmentationarrow-up-right
    thisarrow-up-right
    thisarrow-up-right
    thisarrow-up-right
    TensorFlow Tutorial 4 - Convolutional Neural Networks with Sequential and Functional APIarrow-up-right
    TensorFlow Tutorial 18 - Custom Dataset for Imagesarrow-up-right
    Data Augmentation - Deep Learning with Tensorflow | Ep. 19arrow-up-right
    this notebookarrow-up-right
    herearrow-up-right