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.
Text Classification: AI Techniques and Real-World Applications
Discover AI-powered text classification techniques for spam detection, sentiment analysis, and topic categorization, exploring real-world business applications and best practices.
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.
Using Generative AI to Better Understand B2B Audiences: From Topic Modeling to Text Classification
Unlock the potential of Generative AI and ML for B2B audience understanding. Explore innovative techniques in topic modeling and text classification using LLMs to enhance marketing strategies and data-driven decision-making.
Design and Build Powerful LLM Agents - Valentina Alto
Unlock the potential of LLM agents: explore their design, construction, and evolution from single to multi-agent systems. Gain insights into GenAI workflows and key components of AI agents.
Neural Networks and TensorFlow Crash Course
Comprehensive introduction to neural networks and TensorFlow, covering key concepts, data handling, model building, and practical applications in image and text classification.
Everything You Wanted to Know About Machine Learning but Didn't Know Whom to Ask - Sanjeev Arora
Explore machine learning fundamentals, from text classification to image recognition, with insights on optimization, unsupervised learning, and language models in this comprehensive seminar.
Using Machine Learning to Classify Facebook Posts - UbuConLA 2017
Aprenda a utilizar técnicas de aprendizaje automático para clasificar publicaciones en Facebook, explorando aplicaciones prácticas de inteligencia artificial en redes sociales.
Fine-Tuning T5 for Document Classification - Part 0: Proof of Concept (Español)
Personaliza Flan-T5 para clasificación de documentos usando un dataset pequeño de 1000 documentos en 10 clases.
Azure ML: Fine Tune Foundation Model con Python SDK para LLama2
Aprende a realizar fine-tuning de modelos de lenguaje como Llama2 para clasificación de texto utilizando el SDK de Python de Azure ML Studio.
Fine-tuning Flan-T5 for Text Classification Using MLFlow - Spanish Tutorial
Personaliza un modelo T5 para clasificación de documentos utilizando SequenceClassification y MLflow, mejorando tus habilidades en ciencia de datos y aprendizaje automático.
Fine-Tuning Gemini 1.0 Pro for Text Classification in Spanish - Machine Learning and Data Science
Aprende a ajustar el modelo Gemini Pro 1.0 en Google Vertex AI para clasificación de texto, utilizando la interfaz de usuario y el SDK.
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.
Raising the Quality of Online Conversations with Machine Learning
Explore how The Washington Post uses machine learning to moderate online comments, enhancing digital discourse quality and addressing technical challenges.
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.
Natural Language Processing Breakthroughs in Hebrew and Arabic Linguistics
Discover groundbreaking linguistic annotation techniques for Hebrew and Arabic NLP, exploring morphology, syntax, and dialectical variations through comprehensive datasets and innovative pipelines.
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.
Model Calibration Techniques for Discriminative and Generative Tasks
Explore techniques for aligning confidence predictions with output probabilities in both discriminative and generative models, from basic classification to advanced TrOCR methods.
Creating Ethical Generative AI for Enterprises Using IBM Watsonx.ai
Discover practical strategies for implementing enterprise-level generative AI using IBM Watsonx.ai platform, focusing on ethical deployment, classification tasks, and content generation with various LLM options.
Evaluating LLM Embeddings for Information Retrieval and Multilingual Applications
Explore the latest evaluation of LLM embedding APIs, focusing on OpenAI and Cohere's performance in domain generalization and multilingual retrieval capabilities for information retrieval tasks.
SETFIT Hyperparameter Optimization for SBERT Text Classification - Part 45
Master SETFIT hyperparameter optimization techniques for efficient text classification using Sentence Transformers, focusing on contrastive training and automated parameter tuning for optimal performance.