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Volver a Generative Deep Learning with TensorFlow

Opiniones y comentarios de aprendices correspondientes a Generative Deep Learning with TensorFlow por parte de

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Acerca del Curso

In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an image (eg. swan), and the style of a painting (eg. cubist or impressionist), and combine the content and style into a new image. b) Build simple AutoEncoders on the familiar MNIST dataset, and more complex deep and convolutional architectures on the Fashion MNIST dataset, understand the difference in results of the DNN and CNN AutoEncoder models, identify ways to de-noise noisy images, and build a CNN AutoEncoder using TensorFlow to output a clean image from a noisy one. c) Explore Variational AutoEncoders (VAEs) to generate entirely new data, and generate anime faces to compare them against reference images. d) Learn about GANs; their invention, properties, architecture, and how they vary from VAEs, understand the function of the generator and the discriminator within the model, the concept of 2 training phases and the role of introduced noise, and build your own GAN that can generate faces. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture, and gives them the tools to create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....

Principales reseñas


17 de mar. de 2022

Excellent course - Indepth knowledge delivered by one of the top-developers in an engaginand challenging manner. Superb. Would definitely recommend.


22 de jun. de 2021

Great Course. It would be better to have Capstone Project and Peer Review Process to prove that we are actually able to apply all these techniques.

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26 - 29 de 29 revisiones para Generative Deep Learning with TensorFlow

por Jayasuriya G

14 de jun. de 2021

por Sunder A K

27 de dic. de 2021

The best course for learning the implementation of GANs, stacked and variational autoencoders.

por Vihanga V

25 de mar. de 2022

good course

por Sushanth

21 de oct. de 2021

T​he session on VAE's was interesting, If I could make a suggestion, I would add other generative models, such as Deep Belief Nets, and show how the generated data change from DBNs to VAES to GANS with the same dataset. That would give students a better idea of the tradeoffs involved in each of them.