All Courses

This course discusses deep learning, covering foundational machine learning principles (loss functions, bias-variance trade-off, and optimization) and advanced models (Multilayer Perceptron, Convolutional Neural Networks, Recurrent Neural Networks, Transformers). The course is project-based, emphasizing the application of these techniques to real-world datasets using the deep learning framework PyTorch.