Lectures related to Collaborative filtering

Recommender Systems: Part 1

Introduces recommender systems, collaborative filtering, content-based recommendation, similarity metrics, and matrix factorization.

State Space Models: Expressivity and Transformers

Covers state space models and their expressivity compared to transformers, focusing on attention mechanisms and computational efficiency.

Cloud computing support for IoT

Explores the evolution of cloud computing to support IoT applications and the challenges faced by deep learning algorithms in processing data from smart sensors.

Adaptive Signal Processing: Filtering & Neural Networks

Explores adaptive signal processing, gradient descent, and the LMS algorithm for efficient filtering and neural network training.

Spatial Configuration and Teaching

Explores the impact of spatial configuration on teaching interactions in classrooms, analyzing seating arrangements and teacher movements.

Neuroscience Dataset Recommendation

Covers a tutorial on recommending similar neuroscience datasets using knowledge embeddings.