Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.
Covers the fundamental principles and methods of machine learning, including supervised and unsupervised learning techniques.
Explores interview survey methods, preparation, types of interviews, question formulation, and interaction quality.
Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.
Introduces applied machine learning concepts such as data collection, feature engineering, model selection, and performance evaluation metrics.
