AutoML Faces

Automatically build ML models to perform face recognition.

Automatically build ML models to perform face recognition.

Salient Features

Data Preprocessing and Feature Engineering

• Algorithm automatically transforms user data into a computationally desired form.
• Algorithm identifies features which are redundant or noisy and discards such features during model training.
• It adds new features that are informative and useful to identify hidden patterns in the data.

Hyper-parameter Optimization and Training

• User does not have to provide any Hyper-parameter values.
• Algorithm has in-built fully automated hyper-parameter optimization.
• AutoML Faces uses fast and accurate proprietary learning algorithm.
• Training stops automatically when it detects that the performance of trained model cannot be improved further.
• Alternately, user can also provide a maximum training time, after which the training stops.

Machine Learning and Programming Resource Requirement

• Using AutoML Faces does not require the user to be a Machine Learning or Deep Learning expert.
• The web console makes it very easy for domain experts with no programming experience to train and evaluate ML models.