TELE6500 (Machine Learning for IoT Systems) course reviews and ratings at Northeastern (NEU). Compare professors with RateMyProfessor reviews.
Studies the design, development, rollout, and maintenance of machine learning algorithms for IoT systems, which generate and process time series data under memory and timeliness constraints. Focuses on verticals like Industry 4.0, wearables, and smart grids/homes. Explores the nuances of handling IoT time series data in both edge and cloud computing settings including the preparation, exploration, and feature engineering for sensor data. Covers domain-specific problem classes like forecasting, change point detection, and temporal anomaly detection. Addresses customized performance metrics for time series algorithms. Analyzes deep learning architectures for time series problems using TinyML for embedded devices. Course projects focus on time series, going beyond traditional datasets used in conventional ML classes.
Data updated October 2026.