Essential Building Blocks of Modern Neural Networks

Remi Genet

2025-02-18

Les cours de cette partie sont:

Attention Mechanisms: Learning What to Focus On

Understanding attention mechanisms in neural networks: from basic self-attention to multi-head architectures.

Convolutional Layers: From Images to Time Series

Understanding convolution operations in neural networks and their applications beyond computer vision.

Encoder-Decoder Architectures

Understanding encoder-decoder architectures: principles, mathematics, and applications in sequence-to-sequence tasks.

Neural Network Embeddings: Learning Meaningful Representations

Understanding embeddings in neural networks: from discrete entities to continuous vector spaces.

Residual Connections and Gating Mechanisms

Understanding fundamental building blocks that enable training of deep neural networks: residual connections and gating mechanisms.