Explore >> Select a destination
|
You are here 
|
wtfleming.github.io | ||
| | | | |
glowingpython.blogspot.com
|
|
| | | | | In this post we will see how to create a Multi Layer Perceptron (MLP), one of the most common Neural Network architectures, with Keras. Then... | |
| | | | |
aimatters.wordpress.com
|
|
| | | | | A few weeks ago, it was announced that Keras would be getting official Google support and would become part of the TensorFlow machine learning library. Keras is a collectionof high-level APIs in Python for creating and training neural networks, using either Theano or TensorFlow as the underlying engine. Given my previous posts on implementing an... | |
| | | | |
blog.keras.io
|
|
| | | | | [AI summary] The text discusses various types of autoencoders and their applications. It starts with basic autoencoders, then moves to sparse autoencoders, deep autoencoders, and sequence-to-sequence autoencoders. The text also covers variational autoencoders (VAEs), explaining their structure and training process. It includes code examples for each type of autoencoder and mentions the use of tools like TensorBoard for visualization. The VAE section highlights how to generate new data samples and visualize the latent space. The text concludes with references and a note about the potential for further topics. | |
| | | | |
jan.schnasse.org
|
|
| | | [AI summary] The content discusses website cookies, user consent for analytics and advertising, and privacy policies. | ||
