- Auto encoder decoder are two neural networks that are trained to encode, and then decode the input based on training data and examples. The goal is to compress with little loss and decode to get as close to the original as possible while getting performance gain and efficiency.
- Encode is to obtain a compressed representation of the input
- Decode is takes the representation from encoders and try to reconstruct the original input
- A compressed representation can save space, time, and improve performance of storage, serving and other computer, network tasks
- The depth dimensions should change as follows: 784 inputs > encoding_dim > 784 outputs.
Saturday, March 2, 2019
Autoencoder Decoder Notes Cheatsheet from Udacity Deep Learning Nanodegree
Debug Google Cloud Error - Failed to enable API please make sure you have the IAM permission to enable API
If you are not expecting this message, and think you have the permission to enable API read on. Before using Google Cloud services, genera...
Can hack schools solve Silicon Valley's talent crunch? The truth about coding bootcamps and the students left behind http://t.co/xXNfqN...
In this downtown startup work space design the designers used fat boy bean bags and an extra wide step tiered staircase to create work space...
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...