Keras 2.4.0 Code Snippets for VS code

I found it tedious to rewrite the basic Keras code over and over again. Thats why I built this code snippets to save time. This extension will solve this issue with a simple ! + the name of whatever you are looking for.

Commands

Main Commands

Command	**Description **
!setup	Keras 2.4.0 initial setup
!datasetimg	Load custom image dataset from directory
!datasettext	Load custom textual dataset from directory

Commands for using Keras Datasets

Command	**Description **
!mnist	Loads the dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images.
!fashion	Loads the dataset of 60,000 28x28 grayscale images of 10 fashion categories, along with a test set of 10,000 images.
!cifar10	Loads the dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 10 categories
!cifar100	Loads the dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 100 fine-grained classes that are grouped into 20 coarse-grained classes.
!imbd	Loads the dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 100 fine-grained classes that are grouped into 20 coarse-grained classes.
!boston or !house	Loads the dataset samples containing 13 attributes of houses at different locations around the Boston suburbs in the late 1970s.

Commands for using Keras Optimizers

Command	**Description **
!sgd	Keras 2.4.0 SGD
!adam	Keras 2.4.0 Adam
!rmsprop	Keras 2.4.0 RMSprop
!adadelta	Keras 2.4.0 Adadelta
!adagrad	LKeras 2.4.0 Adagrad
!adamax	Keras 2.4.0 Adamax
!nadam	Keras 2.4.0 Nadam
!ftrl	Keras 2.4.0 Ftrl

Commands for using Keras Losses

Command	**Description **
!sparse	SparseCategoricalCrossentropy
!bin	BinaryCrossentropy
!cat	CategoricalCrossentropy
!poisson	Poisson
!binloss	binary_crossentropy
!catloss	categorical_crossentropy
!sparseloss	sparse_categorical_crossentropy
!poiloss	poisson
!kld	KLDivergence
!kld	kullback_leibler_divergence

Commands for using Keras Accuracy

Command	**Description **
!acc	Accuracy
!binaryacc	BinaryAccuracy
!catagoricalacc	CategoricalAccuracy
!topkacc	TopKCategoricalAccuracy
!sparseacc	SparseTopKCategoricalAccuracy

Commands for using Keras deep learning algorithms

Command	**Description **
!vgg16	Extract features with VGG16
!vgg19	Extract features from an arbitrary intermediate layer with VGG19
!resnet50	Classifies ImageNet classes with ResNet50
!inceptionv3	Fine-tune InceptionV3 on a new set of classes
!inceptionv3custom	Build InceptionV3 over a custom input tensor

Commands for using Keras Transfer Learning Boiler plate of different algorithms

Command	**Description **
!vgg16tl	Transfer Learning using VGG16
!vgg19tl	Transfer Learning using VGG19
!resnet50tl	Transfer Learning using ResNet50
!inceptionv3tl	Transfer Learning using

Requirements

Python 3.5–3.8, Tensorflow 2 and Keras

Known Issues

No known issues so far.

Release Notes

1.0.0

Initial release of Keras 2.4.0 Code Snippets

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