How Many Labelled Examples Do You Need for a BERT-sized Model to Beat GPT4 on Predictive Tasks?
Explore the effectiveness of in-context learning vs. labelled data for predictive tasks, comparing BERT-sized models to GPT-4 in text categorization and entity recognition.
Deep Learning on Electronic Health Records: Unlocking the Power of Clinical Data - Lecture 1
Unlock the power of EHR data using deep learning NLP. Explore frameworks for extracting clinical information, leveraging pretrained transformer models, and addressing challenges in applying language models to healthcare data.
Fine-Tuning BERT for Text Classification - Python Code Tutorial
Dive into fine-tuning BERT for text classification, focusing on phishing URL detection. Learn key concepts and implement Python code to enhance your natural language processing skills.
Transformers and BERT Implementation
Learn to implement Transformers and BERT models, fine-tune pretrained models, and create custom question-answering systems using Hugging Face's powerful NLP tools.
NLP with BERT
Explore transformers and BERT in NLP, covering their architecture, applications, and hands-on implementation using PyTorch. Learn about sequence-to-sequence models, text summarization, and practical use cases.
Emergent Linguistic Structure in Deep Contextual Neural Word Representations - Chris Manning
Explore emergent linguistic structures in deep neural word representations with Stanford's Chris Manning, examining language models, attention mechanisms, and vector space analysis.
Azure Machine Learning - Fine Tune Foundation Model for Text Classification
Aprende a realizar fine-tuning de modelos BERT para clasificación de texto utilizando Azure Machine Learning, mejorando tus habilidades en IA generativa.
Converting BERT to ONNX and Inference with BERTTokenizer for C# - Machine Learning and Data Science
Convierte modelos Bert a ONNX y realiza inferencia con BERTTokenizer en C#. Aprende a implementar aplicaciones prácticas de machine learning.
Large Language Models for Real-World Applications
Explore real-world applications of large language models in this visual overview, covering image captioning, question answering, text generation, and more. Learn about NLP technologies and their potential in various business domains.
Neural Search Improvements with Apache Solr 9.1 - Approximate Nearest Neighbor and Pre-Filtering
Explore neural search in Apache Solr 9.1, including HNSW graph improvements, pre-filtering capabilities, and Deep Learning integrations for enhanced search relevance and efficiency.
Unstable Log Sequence Anomaly Detection - Introducing Vocabulary-Free BERT
Innovative anomaly detection method for unstable log data in cybersecurity, improving on BERT models to reduce false positives and enhance SOC efficiency.
Drug Discovery Generative AI Using Tensor Network GPT or BERT
Explore generative AI applications in drug discovery using GPT and BERT models, focusing on ProtGPT2 for protein sequence generation and ProtBert for protein structure analysis.
Preventing Toxicity and Unconscious Biases Using Large Language and Deep Learning Models
Discover how large language models and BERT transformers can detect and prevent unconscious biases in AI systems, achieving 98.7% accuracy across diverse data sources and cultural contexts.
Optimizing Text Classification in Construction Data Using FastText and BERT Models
Discover how to optimize text classification for construction tenders using fasttext models and BERT, achieving improved accuracy through category merging and probability thresholds for product and supplier predictions.
A Lost Croatian AI Program from the 1950s - Early Machine Translation Development
Discover the fascinating history of Croatian AI pioneers and their groundbreaking 1950s machine translation system, exploring parallels with modern transformer models like BERT and GPT.
Generative Interactive Environments (GENIE) - Creating Synthetic Video Game Worlds
Explore GENIE AI's groundbreaking technology for generating interactive video environments, featuring advanced neural networks and transformers for synthetic world creation.
AGENTiGraph: Integrating LLM-based Multi-Agent Systems with Knowledge Graphs
Explore how AGENTiGraph combines seven specialized AI agents with knowledge graphs to enhance LLM capabilities, focusing on entity mapping, reasoning, and complex query handling.
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.
Train a Domain-Specific BERT Tokenizer Using SBERT - Part 50
Master BERT tokenizer training for scientific domains using SBERT, focusing on byte-pair encoding and specialized pre-training for complex domain-specific knowledge like bio-pharmacological content.
Domain-Specific AI Models - Creating Customized BERT and SBERT Models for Business Applications
Discover how to effectively train and fine-tune BERT and SBERT models for specialized domains, focusing on medical and biochemical terminology, with practical solutions for business applications.
Feature Vectors - Understanding BERT and SBERT Transformer Models
Dive into feature vectors and their crucial role in BERT and SBERT transformer models, exploring vectorization techniques, Python implementation, and practical applications in NLP.