Automated Machine Learning (AutoML) is a process of applying full machine learning pipeline in automatic way. The AutoML solution can do feature preprocessing and eningeering, algorithm training and hyperparameters selection.
Build great machine learning models without coding!
The service works with structured data. It accepts CSV (Comma Separated Values) files as input. File used for training should have a target column. User uploads data file to mljar service. You can find example data files in this link.
For each data uploaded to the service the following statistics are computed:
For each column (feature) you can:
To train machine learning model you need to create ML experiment. It is easy and done with few-clicks. Most of the parameters which can be selected are set to smart defaults. You are required to select a training data.
The service store information about each model and its training process. You can check:
To prevent overfitting the early stopping is used on all models. The model internal architecture stored in the service is always from best iteration number.
You can check the importance of your features for algorithms:
There are many options how you can use your model: