Attention Mechanisms Courses and Certifications

Yannic Kilcher

Rethinking Attention with Performers

Explore a novel approach to efficient attention mechanisms in Transformers using random positive orthogonal features, enabling linear-time approximation of attention matrices for scalable deep learning architectures.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Yannic Kilcher

Object-Centric Learning with Slot Attention

Explanation of a novel deep learning module for object-centric visual scene understanding. Covers architecture, algorithm, experiments, and implications of Slot Attention for improved object recognition and reasoning.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Yannic Kilcher

Train Short, Test Long - Attention With Linear Biases Enables Input Length Extrapolation

ALiBi: A novel attention mechanism enabling transformers to process longer sequences than trained on. Uses linear biases instead of position encodings, improving efficiency and extrapolation capabilities.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Attention Mechanism

Learn about the attention mechanism in neural networks, its applications in machine learning tasks, and how it enhances performance in various AI applications.

• Google Cloud Skills Boost
• 30 minutes
• On-Demand
• Free Certificate

Serrano.Academy

The Math Behind Attention Mechanisms

Demystify attention mechanisms in Transformer models through visuals, examples, and mathematical explanations, focusing on embeddings, similarity, and key-query-value matrices.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Aleksa Gordić - The AI Epiphany

Flash Attention 2.0 with Tri Dao - Discord Server Talks

Explore Flash Attention 2.0 with author Tri Dao, covering its motivation, improvements, and future directions. Gain insights into memory bottlenecks and IO awareness in attention mechanisms for long sequences.

• YouTube
• 1 hour
• On-Demand
• Free Video

Pascal Poupart

CS480-680 Lecture 19 - Attention and Transformer Networks

Explore attention mechanisms, transformer networks, and their applications in machine learning, including multihead attention and normalization techniques.

• YouTube
• 1 hour 23 minutes
• On-Demand
• Free Video

Pascal Poupart

Memory Augmented Networks

Learn about memory augmented networks, including architecture, attention mechanisms, and applications in machine translation, with a focus on improving generalization in deep learning models.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Alfredo Canziani

CNN Applications, RNN, and Attention

Explore CNN applications in digit recognition, object detection, and semantic segmentation. Dive into RNNs, addressing their challenges with attention mechanisms, GRUs, LSTMs, and Seq2Seq models.

• YouTube
• 1 hour 29 minutes
• On-Demand
• Free Video

Yannic Kilcher

Attention Is All You Need

Explore the groundbreaking Transformer architecture, revolutionizing sequence transduction with attention mechanisms. Learn its superior performance in machine translation and generalization to other NLP tasks.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Simons Institute

Fast Attention Requires Bounded Entries

Explore the relationship between fast attention mechanisms and bounded entries in machine learning, with insights from Josh Alman's research on sketching and algorithm design.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Attention Mechanism

Explore the attention mechanism in neural networks, enhancing focus on specific input sequence parts for improved machine learning performance in translation, summarization, and question answering.

• Pluralsight
• 6 minutes
• On-Demand
• Free Trial Available

Institute for Pure & Applied Mathematics (IPAM)

Fast Multipole Attention: A Divide-and-Conquer Attention Mechanism for Long Sequences

Innovative divide-and-conquer strategy for efficient attention in long sequences, reducing complexity while maintaining global receptive field. Potential to enhance large language models with extended context processing.

• YouTube
• 42 minutes
• On-Demand
• Free Video

Data Science Courses

Attention Mechanism and Self-Attention in Deep Learning - Lecture 9

Dive into attention mechanisms and self-attention concepts in deep learning, exploring their revolutionary impact on NLP and discovering practical applications in sequence models.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

UofU Data Science

Pairwise Feature Importance and Effective Attention in Self-Attention Networks

Dive into advanced concepts of attention mechanisms, exploring effective attention computation, norm-based analysis, and practical applications in neural networks.

• YouTube
• 36 minutes
• On-Demand
• Free Video