TensorFlow 2 Beginner Course
Comprehensive introduction to TensorFlow 2.0 and Keras, covering key concepts and practical applications in deep learning through hands-on projects and real-world examples.
TensorFlow for JavaScript - TensorFlow at O’Reilly AI Conference, San Francisco '18
Explore TensorFlow.js: Learn to train, deploy, and perform transfer learning in browsers and Node.js. Includes live demos and practical insights for machine learning workflows.
Introduction to Transfer Learning
Explore transfer learning to adapt pre-trained networks for microscopy applications, enhancing accuracy with limited labeled data and reducing training time.
The Carbonate Forum 2021 - Artificial Intelligence in Carbonates
Explore AI applications in carbonate geology, covering microcrystal segmentation and CNN architectures for core classification. Gain insights into cutting-edge techniques and their geological implications.
Transfer Learning: Applications for Natural Language Understanding in Business
転移学習の実用化：AIシステムの知見を活用し、カスタマーサービス、検索、セルフヘルプ、金融分野での自然言語理解を向上。トレーニングデータ不足の課題に対する革新的なソリューション。
Transfer Learning, Covariant Learning and Parallel Transport
Explore transfer learning concepts, including dual algorithms, early time series classification, and connections to analogical reasoning and online learning. Gain insights into bias, information cost, and guarantees.
LLMOps: Personalizar ViT Classifier con tu Propia Data y Docker Inference
Personaliza un Vision Transformer con tu dataset, crea un docker y un punto de inferencia con FastAPI para clasificación de imágenes.
LLMOps: Personalizar Video Classifier (ViViT) con tu Propia Data
Personaliza un Video Vision Transformer (ViViT) con tu propio dataset utilizando un modelo preentrenado de Google y entrena un clasificador personalizado.
Fine-Tuning ViT Classifier for Retinal Image Detection - Part 2 (Español)
Personaliza un Vision Transformer para clasificar imágenes de retina, detectando ojos enfermos usando el dataset EyeQ. Aprende a ajustar modelos pre-entrenados para tareas específicas.
Microsoft AI: MLNet Framework en C# - Transfer Learning para Clasificación de Imágenes
Integra MLNet con TensorFlow para clasificar imágenes de superficies de cemento mediante transfer learning y la API de ML.NET Image Classification Library.
Fine-Tuning ViT Classifier for Retina Images and Converting to ONNX Format - Part 3
Personaliza un Vision Transformer con tu dataset de imágenes de retina y conviértelo a formato ONNX para optimizar el rendimiento y la portabilidad.
Artificial Intelligence per Kilowatt-Hour - Max Welling, University of Amsterdam
Explore cutting-edge AI efficiency: compressing neural nets, low-precision computing, and spiking networks to maximize intelligence per kilowatt-hour as AI moves to edge devices.
Training Highly Generalizable Biomedical Image Segmentation Models with Very Few Annotations
Learn highly generalizable biomedical image segmentation techniques using minimal annotations, focusing on efficient model training and performance optimization for medical imaging tasks.
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Explore vision-language-action models for robotic control, enhancing generalization and semantic reasoning through Internet-scale data integration and end-to-end training.
RoboCat - A Self-Improving Generalist for Robotic Manipulation
Explore RoboCat, a multi-embodiment, multi-task generalist agent for robotic manipulation. Learn about its ability to generalize across tasks and robots, and its potential for autonomous improvement.
Deep Learning and Transfer Learning for NLP
Explore deep learning and transfer learning for NLP with expert Dipanjan Sarkar. Gain insights on challenges, deployment, popular models, tools, and recent advances in multilingual AI and model interpretability.
Data Efficiency Through Transfer Learning - Eddie Du
Explore data-efficient transfer learning techniques to overcome limited training data, including instance-based approaches and differentially private aggregation for enhanced model performance and privacy preservation.
Mastering Multilingual Recommender Systems - Grandmaster Series
Explore NVIDIA Merlin team's winning approach in Amazon KDD Cup 2023, featuring innovative techniques for multilingual e-commerce product recommendations and next product title generation.
Deep Learning Across Label Confidence Distribution via Transfer Learning
Improve predictive power in noisy data systems using Filtered Transfer Learning (FTL). Learn to handle datasets with varying label confidence through hierarchical fine-tuning and iterative filtering.
A Cabinet of Deep Learning Curiosities - Unconventional Techniques and Overlooked Methods
Explore unconventional deep learning techniques, from obscure hacks to overlooked best practices, that have proven surprisingly effective in real-world projects.
Mathematical Framework and Numerical Aspects of Adapted Optimal Transport
Explore mathematical frameworks for transfer learning and numerical aspects of adapted optimal transport in financial mathematics and engineering through expert talks from leading researchers.