One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Let’s imagine a fictional company, Global Retail Corporation, a multinational retail chain struggling with its initial approach to AI integration. They built custom generative AI applications on their ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...