Self-Attention Courses and Certifications

Graham Neubig

Neural Nets for NLP 2017 - Attention

Comprehensive exploration of attention mechanisms in neural networks for NLP, covering various types, improvements, and applications, with a focus on the Transformer model.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Prodramp

Prompt Engineering - Understanding Large Language Models with ChatGPT

Explore large language models and ChatGPT through prompt engineering. Learn about transformer architecture, text embedding, self-attention, and key deep learning methods with practical Python examples.

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

Meta

New Approaches to Image and Video Reconstruction Using Deep Learning

Explore cutting-edge deep learning techniques for image and video enhancement, including colorization and resolution improvement, using efficient PyTorch-based tools trainable on a single GPU.

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

Edan Meyer

Recreate Google Translate - Model Training

Explore model training and testing for Neural Machine Translation, recreating Google Translate using mT5 and Hugging Face. Practical implementation and demo of multilingual translations.

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

Andrej Karpathy

Let's Build GPT - From Scratch, in Code, Spelled Out

Comprehensive tutorial on building a GPT model from scratch, covering key concepts like self-attention, multi-headed attention, and transformer architecture. Includes practical coding examples and insights into modern language models.

• YouTube
• 1 hour 56 minutes
• On-Demand
• Free Video

Graham Neubig

CMU Multilingual NLP - Machine Translation-Sequence-to-Sequence Models

Explore conditional language modeling, sequence-to-sequence models, generation methods, attention mechanisms, and transformers in multilingual natural language processing.

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

Graham Neubig

Neural Nets for NLP 2020 - Document Level Models

Explore document-level NLP techniques including language modeling, coreference resolution, and discourse parsing. Learn advanced approaches for handling long-range dependencies and entity relationships in text.

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

Graham Neubig

Neural Nets for NLP 2021 - Document-Level Models

Explores advanced NLP techniques for document-level tasks, including long-document modeling, entity coreference, and discourse parsing, with a focus on neural network approaches and their applications.

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

CodeEmporium

Informer: Complete Code from Scratch - Time Series Transformer Analysis

Line-by-line exploration of the time series transformer, focusing on implementation details and code structure for deep learning enthusiasts and practitioners.

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

CodeEmporium

Informer Architecture Explained - Complete Guide

Comprehensive exploration of Informer encoder architecture, detailing its components and implementation for advanced time series forecasting and sequence modeling tasks.

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

CodeEmporium

Informer Encoder Architecture Explained

Explore the Informer Encoder architecture, its key components, and implementation details for advanced time series forecasting and sequence modeling tasks.

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

Valerio Velardo - The Sound of AI

Transformers Explained - Part 1: Generative Music AI

Comprehensive exploration of transformer architectures in AI, covering intuition, theory, and mathematical formalization, with focus on their application in music and audio processing.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video

AutoML Seminars

Discovering Black-Box Optimizers via Evolutionary Meta-Learning

Delve into evolutionary meta-learning techniques for discovering black-box optimizers, exploring advanced concepts in evolution strategies and genetic algorithms through self-attention architectures.

• YouTube
• 50 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