https://github.com/ax-va/tensorflow2-keras-michelucci-2022

Examples based on Umberto Michelucci's book: "Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python", Second Edition, Apress, 2022
https://github.com/ax-va/tensorflow2-keras-michelucci-2022

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Examples based on Umberto Michelucci's book: "Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python", Second Edition, Apress, 2022

• Host: GitHub
• URL: https://github.com/ax-va/tensorflow2-keras-michelucci-2022
• Owner: ax-va
• Created: 2022-07-05T07:14:54.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-08T19:37:06.000Z (about 1 year ago)
• Last Synced: 2023-10-08T20:29:47.315Z (about 1 year ago)
• Language: PureBasic
• Homepage:
• Size: 16 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# TensorFlow2-Keras-Michelucci-2022

Examples based on the Umberto Michelucci's book: "Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python", Second Edition, Apress, 2022

## Online sources

Book's online version:

https://adl.toelt.ai

Original GitHub by TOELT LLC:

https://github.com/toelt-llc/BOOK-ADL-Book-2nd-Ed

## Datasets

Radon activity: http://www.stat.columbia.edu/~gelman/arm/examples/radon/

BCCD (blood cells): https://github.com/ax-va/BCCD_Dataset/tree/master/BCCD/Annotations/

Zalando clothes images: https://www.kaggle.com/zalando-research/fashionmnist/data; https://github.com/zalandoresearch/fashion-mnist (convert with  https://pjreddie.com/projects/mnist-in-csv/); or download from keras.datasets (used in code):

```python

(x_train, y_train), (x_test, y_test) = keras.datasets.fashion_mnist.load_data()

```

MNIST handwritten digits: http://yann.lecun.com/exdb/mnist/; or download from Keras: 

```python

(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()

```

Boston area housing: http://lib.stat.cmu.edu/datasets/boston; https://archive.ics.uci.edu/ml/machine-learning-databases/housing/

 

http://www.image-net.org/

## Useful links

IPython documentation:

https://ipython.readthedocs.io/en/st

Kaggle competitions:

https://www.kaggle.com/competitions