In this course, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.
Throughout the course, you will learn data science techniques for collecting data and develop an understanding of learning algorithms to train basic machine learning models.
Learn about real-word industry applications of TinyML as well as Keyword Spotting, Visual Wake Words, Anomaly Detection, Dataset Engineering, and Responsible Artificial Intelligence.
By the end of the course, students will be able to understand and implement the state-of-the-art multi-task learning and meta-learning algorithms and be ready to conduct research on these topics.
BREAKING: The next BIG leap in AI architecture just dropped.
This new 27 million parameter model just outsmarted Claude, Gemini, Grok 4, and o3-mini.
HRM is a brain-inspired system architecture for layered reasoning and self-evolving intelligence.
Here’s how it works:
When I first read about HRM (Hierarchical Reasoning Model), I was skeptical.
How can something this small, with only 27 million parameters, outperform Claude 3.5 on the ARC test, solve 30x30 mazes, and work without any step-by-step instructions?