Hands-On Deep Learning for IoT

AE classifier

As described in Chapter 2, Deep Learning Architectures for IoT, AEs are special types of neural networks that learn automatically from the input data. AEs consists of two components: an encoder and a decoder. An encoder compresses the input into a latent-space representation. Then, the decoder part, tries to reconstruct the original input data from that representation:

• Encoder: Encodes or compresses the input into a latent-space representation using a function known as
• Decoder: Decodes or reconstructs the input from the latent space representation using a function known as

So, an AE can be described by a function of , where ...