Personalized automated machine learning

A computer-implemented method for personalizing machine learning models for at least one user of an automated machine learning system, the machine learning models being generated by the automated machine learning system, the method comprising:

• obtaining a first user profile dataset for training a first neural network, the first user profile dataset containing data related to the at least one user;
• obtaining a first model profile dataset for training a second neural network, the first model profile dataset containing one or more attributes related to the machine learning models;
• obtaining a user-model relationship dataset for training a third neural network;
• inputting, for training the first neural network, the first user profile dataset to the first neural network, the first neural network generating a first training output data;
• inputting, for training the second neural network, the first model profile dataset to the second neural network, the second neural network generating a second training output data;
• inputting, for training the third neural network, the first training output data and the second training output data to an input layer of the third neural network;
• inputting, for training the third neural network, the user-model relationship dataset to an output layer of the third neural network;
• tuning hyperparameters for the first, second, and third neural networks for testing and training the neural networks;
• once the first, second and third neural networks are trained, inputting a second user profile dataset to the trained first neural network, the trained first neural network generating a first output data;
• inputting a second model profile dataset to the trained second neural network, the trained second neural network generating a second output data;
• inputting the first output data and the second output data to the trained third neural network, the trained third neural network generating a third output data, the third output data including a relevance score for each of the users for each of the machine learning models;
• and
• displaying a list of machine learning models associated with the at least one user, with each of the machine learning models showing the relevance score.