Transformers Courses and Certifications

Institute for Pure & Applied Mathematics (IPAM)

Exploiting Low-Dimensional Data Structures and Understanding Neural Scaling Laws of Transformers

Explore how low-dimensional data structures explain transformer scaling laws through statistical estimation theory and empirical validation with large language models.

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

USC Information Sciences Institute

What Transformers Can and Can't Do - A Logical Approach

Explore the theoretical foundations of transformers through formal logic, uncovering their expressivity limits and capabilities in this research seminar by David Chiang.

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

AI Bites

Getting Started with HuggingFace Transformers - Pipeline, Tokenizer, and Model Development

Master HuggingFace Transformers library fundamentals, from pipelines and tokenizers to models and Hub integration, enabling you to effectively work with and fine-tune Large Language Models.

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

Discover AI

The Art of Text to Vector Transformation - A Comprehensive Look at AI and NLP Transformers

Dive into the fundamentals of converting text to mathematical vectors, understanding tokenization methods like BERT and BPE for NLP applications and AI transformer models.

• YouTube
• 13 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

Valerio Velardo - The Sound of AI

Transformers for Generative Music AI - Part 2: Decoder and Music Generation

Explore transformer architecture for music AI, focusing on decoder components, masked attention, and practical tips for generating music. Dive into future research and neuro-symbolic integration for robust music generation.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Data Council

HuggingFace and Ray AIR Integration: A Python Developer's Guide to Scaling Transformers

Scale Hugging Face Transformers beyond a single machine using Ray AI Runtime. Learn to implement end-to-end workflows for advanced ML models, from data ingest to fine-tuning and serving.

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

Data Science Conference

Optimizing Workloads with Transformers and Diffusers

Discover how Transformers and Diffusers architectures can optimize workloads, enhance efficiency, and revolutionize both natural language processing and computer vision applications in deep learning.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

Data Science Conference

Transformers for Extractive Text Summarization - Data Science Applications

Master effective data storytelling techniques and learn to bridge communication gaps between data scientists and product managers while enhancing collaboration and presentation skills.

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

Simons Institute

How Transformers Learn Causal Structure with Gradient Descent

Delve into the mathematical foundations of how transformer models learn and encode causal relationships through self-attention mechanisms and gradient-based training algorithms.

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

INI Seminar Room 2

Clustering Dynamics in Mean-Field Models of Transformers

Explore clustering dynamics in mean-field models of Transformers with Dr. Andrea Agazzi, examining mathematical foundations and prediction uncertainty in machine learning architectures.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Free Video

INI Seminar Room 2

Clustering Dynamics in Mean-Field Models of Transformers

Explore clustering dynamics in mean-field models of Transformers with Dr. Andrea Agazzi from Universität Bern in this mathematical sciences seminar on prediction uncertainty.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

INI Seminar Room 2

Clustering Dynamics in Mean-Field Models of Transformers

Explore clustering dynamics in mean-field models of Transformers with Dr. Andrea Agazzi from Universität Bern in this mathematical sciences seminar on prediction uncertainty.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Simons Institute

Transformers Can Learn Compositional Function

Explore how transformers learn compositional functions with Jason Lee from Princeton University in this Simons Institute talk on the future of language models.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Simons Institute

Reducing the Dimension of Language: A Spectral Perspective on Transformers

Explore a novel approach to sequence modeling that leverages dynamical systems principles to achieve long-range memory, fast inference, and provable robustness beyond traditional Transformers.

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