My Blog

Author: Awais Farooq

  • EfficientNetV2 B0 to B3 and S, M, L

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    Awais Farooq
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    EfficientNetV2B0 function Instantiates the EfficientNetV2B0 architecture. Reference This function returns a Keras image classification model, optionally loaded with weights pre-trained on ImageNet. For image classification use cases, see this page for detailed examples. For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning. Note: each Keras Application expects a specific kind of…

  • EfficientNet B0 to B7

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    Awais Farooq
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    EfficientNetB0 function Instantiates the EfficientNetB0 architecture. Reference This function returns a Keras image classification model, optionally loaded with weights pre-trained on ImageNet. For image classification use cases, see this page for detailed examples. For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning. Note: each Keras Application expects a specific kind of…

  • Xception

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    Awais Farooq
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    Xception function Instantiates the Xception architecture. Reference For image classification use cases, see this page for detailed examples. For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning. The default input image size for this model is 299×299. Note: each Keras Application expects a specific kind of input preprocessing. For Xception, call keras.applications.xception.preprocess_input on…

  • California Housing price regression dataset

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    Awais Farooq
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    load_data function Loads the California Housing dataset. This dataset was obtained from the StatLib repository. It’s a continuous regression dataset with 20,640 samples with 8 features each. The target variable is a scalar: the median house value for California districts, in dollars. The 8 input features are the following: This dataset was derived from the 1990 U.S.…

  • Fashion MNIST dataset, an alternative to MNIST

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    Awais Farooq
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    load_data function Loads the Fashion-MNIST dataset. This is a dataset of 60,000 28×28 grayscale images of 10 fashion categories, along with a test set of 10,000 images. This dataset can be used as a drop-in replacement for MNIST. The classes are: Label Description 0 T-shirt/top 1 Trouser 2 Pullover 3 Dress 4 Coat 5 Sandal 6…

  • Reuters newswire classification dataset

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    Awais Farooq
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    load_data function Loads the Reuters newswire classification dataset. This is a dataset of 11,228 newswires from Reuters, labeled over 46 topics. This was originally generated by parsing and preprocessing the classic Reuters-21578 dataset, but the preprocessing code is no longer packaged with Keras. See this GitHub discussion for more info. Each newswire is encoded as a list of…

  • IMDB movie review sentiment classification dataset

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    Awais Farooq
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    load_data function Loads the IMDB dataset. This is a dataset of 25,000 movies reviews from IMDB, labeled by sentiment (positive/negative). Reviews have been preprocessed, and each review is encoded as a list of word indexes (integers). For convenience, words are indexed by overall frequency in the dataset, so that for instance the integer “3” encodes the 3rd…

  • CIFAR100 small images classification dataset

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    Awais Farooq
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    load_data function Loads the CIFAR100 dataset. This is a dataset of 50,000 32×32 color training images and 10,000 test images, labeled over 100 fine-grained classes that are grouped into 20 coarse-grained classes. See more info at the CIFAR homepage. Arguments Returns x_train: uint8 NumPy array of grayscale image data with shapes (50000, 32, 32, 3), containing the training data. Pixel…

  • CIFAR10 small images classification dataset

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    Awais Farooq
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    load_data function Loads the CIFAR10 dataset. This is a dataset of 50,000 32×32 color training images and 10,000 test images, labeled over 10 categories. See more info at the CIFAR homepage. The classes are: Label Description 0 airplane 1 automobile 2 bird 3 cat 4 deer 5 dog 6 frog 7 horse 8 ship 9 truck Returns…

  • MNIST digits classification dataset

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    Awais Farooq
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    load_data function Loads the MNIST dataset. This is a dataset of 60,000 28×28 grayscale images of the 10 digits, along with a test set of 10,000 images. More info can be found at the MNIST homepage. Arguments Returns x_train: uint8 NumPy array of grayscale image data with shapes (60000, 28, 28), containing the training data. Pixel values range from 0…