Building MLM Training Input Pipeline - Transformers From Scratch
Learn to create a complex input pipeline for Masked Language Modeling, transforming raw OSCAR data into a DataLoader ready for training transformer models from scratch.
Sentiment Analysis on Any Length of Text With Transformers - Python
Learn to perform sentiment analysis on long texts using transformers in Python, overcoming token limitations through chunking and processing techniques for NLP tasks.
NER Powered Semantic Search in Python
Learn to implement NER-powered semantic search in Python using Transformers, Sentence Transformers, and Pinecone. Explore dataset preparation, entity creation, embedding generation, and querying techniques for efficient information retrieval.
Differentiable Associative Memories, Attention, and Transformers
Explore differentiable associative memories, attention mechanisms, and transformers. Learn about energy minimization, planning, and various transformer applications in machine learning and AI.
Deep Learning for Natural Language Processing
Explore NLP architectures, transformers, language models, and advanced techniques for text generation and embedding learning in this comprehensive deep learning lecture.
End-to-End Object Detection with Transformers
Learn about cutting-edge object detection using Transformers, exploring architecture, bipartite matching, oppositional encoding, and attention scores in this comprehensive tutorial.
All Things VQGAN - VQ-VAE and GAN with Transformers and Codebook Interaction
Explore VQ-VAE and GAN integration with Transformers in VQGAN, focusing on codebook interaction and new image generation techniques.
AI-Guided Nonlinear Optimization for Real-World Problems - IPAM at UCLA
Explore AI-guided optimization techniques for complex real-world problems, focusing on nonconvex objectives and slow-to-evaluate functions in applications like embedding table sharding and antenna design.
Hugging Face Agents - Full Tutorial
Explore Hugging Face's new Transformers Agents API for natural language-driven multimodal tasks, including image generation and text-to-speech, with extensible tools and practical examples.
An Introduction to Transfer Learning in NLP and HuggingFace
Explore breakthroughs in NLP through transfer learning and Transformers. Discover HuggingFace's open-source tools for democratizing NLP research and development.
Delta Keyword Transformer: Bringing Transformers to the Edge Through Dynamically Pruned Multi-Head Self-Attention
Explore cutting-edge techniques for optimizing Transformers in edge computing, focusing on the Delta Keyword Transformer and its dynamic pruning approach for efficient multi-head self-attention.
Integrating Feast Online Feature Store with KFServing
Explore integrating Feast online feature store with KFServing for efficient machine learning model serving, featuring insights from IBM experts on deployment and implementation.
Transformers: Introduction and Fundamentals - Day 1
Explore the fundamentals of Transformers, a powerful deep learning architecture revolutionizing natural language processing and beyond.
Customizing Kustomize with Client-Side Custom Resources
Explore Kustomize extensions for declarative Kubernetes configuration management, including custom resources, practical applications, and best practices for building effective extensions.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 9
Explore advanced machine learning techniques for high energy physics: Deepsets, Graph Neural Networks, and Transformers. Gain insights into cutting-edge data analysis methods for particle physics research.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 4
Explore advanced machine learning techniques for high energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 2
Explore advanced deep learning architectures like Deepsets, Graph Neural Networks, and Transformers for high-energy physics applications in this comprehensive lecture.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 1
Explore advanced machine learning techniques for high-energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.
NeurIPS 2023 Research Highlights - Poster Session 2
Explore cutting-edge AI research from NeurIPS 2023, covering topics like RNN training, image editing, language models, transformers, geo-localization, and hardware resilience in image classifiers.
Coding a ChatGPT-Like Transformer From Scratch in PyTorch
Step-by-step tutorial on building a ChatGPT-like Transformer from scratch in PyTorch, covering data preparation, position encoding, attention mechanisms, and model training for natural language processing.
State Space Models: Advancements and Applications in AI - Featuring Albert Gu and Karan Goel
Explore state space models with experts Albert Gu and Karan Goel, discussing their groundbreaking research, real-time demos, and how SSMs compare to transformers in AI applications.