Deep Learning Fundamentals

Dive deep into the internals of Optimization and Training by comprehensively studying gradient descent and backpropagation and advanced optimizers and regularization.

Dive deep into the internals of Convolutional Neural Networks by comprehensively studying convolutions and pooling and classic cnn architectures.

Dive deep into the internals of Advanced Computer Vision by comprehensively studying object detection basics and transfer learning.

Master the practical implementation of Sequence Models by comprehensively studying recurrent neural networks (rnns) and lstms and word embeddings.

Develop an intuitive mental model for Transformers and Generative Models by comprehensively studying attention mechanisms and transformers and introduction to generative models.