After training, the autoencoder can be split into an encoder and a decoder ... I have also written about my experiences using keras-molecules
What you'll learn
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Master Autoencoders and its different models using Keras
.Autoencoders are a very popular neural network architecture in Deep
Learning. It consists of 2 parts - Encoder and Decoder. Encoder encodes
the data into some smaller dimension, and Decoder tries to reconstruct
the input from the encoded lower dimension. The lowest dimension is
known as Bottleneck layer. So, it can be used for Data compression.In
this course we explore the different types of Autoencoders, starting
from simple to complex models. We'll also look at how to implement
different Autoencoder models using Keras, which one of the most popular
Deep Learning frameworks.
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