Covers CNNs, RNNs, SVMs, and supervised learning methods, emphasizing the importance of tuning regularization and making informed decisions in machine learning.
Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.
Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.
