Automated Machine Learning is the end-to-end process
of applying machine learning in an automatic way
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.
The AutoML saves a lot of time for Data Scientist. You don't need to manually preprocess the data, convert between formats, check for the ML packages versions and track ML hyperparameters & experiments.
The most of ML pipeline is automated. You don't need to worry about manually setting the ML experiments and results tracking. The feature engineering, hyperparameters tuning, model training and documentation - all done in automated manner. Enjoy the results!
The mljar AutoML framework provides state-of-the-art performance. Use advanced feature engineering, ensemble building and model stacking to build the most accurate ML systems. All in the automated way.
Compare the popular AutoML frameworks on challenging Kaggle datasets
on
binary, multiclass classification, and regression Machine Learning tasks.
The AutoML will replace data scientists that are not using AutoML tools with the ones that do.
The data scientist with AutoML tools is more productive and can deliver results much faster.
What is more, the AutoML enables many of the software developers and data analysts
without
classical ML training to
use Machine Learning methods in the organizations to solve real problems.
