Automated Machine Learning
Automated Machine Learning is the end-to-end process
of applying machine learning in an automatic way.
The complete AutoML pipeline usually consists of:
data preprocessing,
feature engineering,
feature selection,
model training,
hyperparameter tuning,
algorithm selection.
The outlined steps can be very time-consuming.
There is a lot of ML algorithms that can be applied at each step of the analysis.
The difficulty in manual construction of ML pipeline lays in the difference
between data formats, interfaces and computational-intensity of the Machine Learning algorithms.
The Automated Machine Learning solution aims to solve this problem
by checking automatically different combinations of the ML algorithms.
The process of automated machine learning is controlled by statistical algorithm.