- 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
Data cleaning Missing data Outlier Others: duplicates, typos, special characters Strategy for missing data: imputation, mean, median...
This review is updated continuously throughout the program. Yay I just joined the Udacity Nanodegree for Digital Marketing! I am such an Uda...
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...
In this exercise 8/12, Codecademy requires you to do some basic arithmetics using Java. Use the plus symbol + for addition, the minus symbol...