Examples of using MLJAR python API
Examples how MLJAR python API can be used for building machine learning models:
- auto-trading-numerai is an example of stock market prediction based on raw data from Numer.ai. It is a task of building binary classifier. In the example we run Xgboost, LightGBM and Neural Network models.
- UCI-Adult is an example of model which predicts whether income exceeds $50K/yr based on census data. It is a task of binary classification. In the example we run Random Forest, LightGBM and Xgboost models.
What's going on?
- In this examples you load example datasets and build machine learning models with MLJAR.
- To build models with MLJAR you are using our super easy python API.
- MLJAR will check for you many machine learning algorithms, tune each of algorithm and create an ensemble.
- You can view details of your models on MLJAR website after login to your account.