Hey fellow coders,
In the midst of coding and deploying, I took a break to celebrate a special milestone - my son Donnie's first birthday. It's like watching a project come to life, from the initial launch (his birth) to this exciting version 1.0 update.
Do you find it so complicated to set up Apache Airflow for using right away? Don't worry, I can show you a simple and fast way! Are you ready? Then please take a look the instruction below.
docker-compose.ymlcurl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.0.2/docker-compose.yaml' |
Source: https://www.robots.ox.ac.uk/~vgg/data/pets/
An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction, by training the network to ignore signal “noise”. Along with the reduction side, a reconstructing side is learned, where the autoencoder tries to generate from the reduced encoding a representation as close as possible to its original input, hence its name.
