Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.
Explores generalization in machine learning, focusing on underfitting and overfitting trade-offs, teacher-student frameworks, and the impact of random features on model performance.
Delves into the legal aspects of real-time bidding in online advertising, focusing on data protection laws, consent management challenges, and recent legal implications.