Tech blog
Show category:
-
All
{
AI
Artificial Intelligence
Business insights
Category 1
Category 2
Category 3
Classification
Classifier
Fraud
Generative AI
Geometric deep learning
Large language models
Machine learning
Market segmentation
Named Entity Recognition
Natural language processing
NLP
Object detection
Recommendation System
Retrieval Augmented Generation
Segmentation
Sentiment Analysis
Speech Recognition
Synthetic data
Topic Modeling
User Engagement
User segmentation
December 01, 2021
Read more
Zero-Shot Learning in NLP
Recent transformer-based language models, such as RoBERTa, ALBERT, and OpenAI GPT, have shown a powerful ability to learn universal language representations. However, in many real-world scenarios, the lack and cost of labeled data is still a limiting factor.
Zero-shot learning (ZSL) is a form of transfer learning that aims to learn patterns from labeled data in order to detect classes that were never seen during training. As the lack of labeled data and scalability is a regular problem in machine learning applications, ZSL has gained much attention in recent years thanks to its ability to predict unseen classes.
