This course is designed for those who have a solid understanding of the fundamentals explored in the ML 101 Course. You will delve into topics such as reinforcement learning, autoregressive models and recurrent neural networks.
The course emphasizes hands-on learning, and each lesson has a practical code example. To learn about the theory, check out the resources in the README file of each lesson. By the end of this course, you will gain a deep technical understanding of machine learning and its applications. This course is perfect for those looking to take their machine learning expertise to the next level and build a foundation for specialized applications or advanced research.