Areas of knowledge in AI

• Data processing: ingest, cleaning, visualization, normalization, feature selection, feature extraction, dimensionality reduction, data augmentation, discretization.

• Machine learning algorithms: classification, anomaly detection, forecasting, clustering, deep learning, reinforcement learning, LLMs, transformers,  transfer learning.

• Model validation and evaluation: parameterization, evaluation metrics, statistical tests.

• Research: design of new algorithms and architectures, writing scientific papers, publication process, presentation and dissemination of results in top quality sources.

• Specific ML areas I have worked in: Anomaly Detecion, Natural Language Processing, Predictive Maintenance, Edge Computing, Federated Learning.