The main difference between Natural Language Processing (NLP) and computer vision lies in the type of data they process. NLP focuses on understanding and generating human language, analyzing textual data for tasks like translation, sentiment analysis, and text summarization. Computer vision, on the other hand, deals with visual data such as images and videos, performing tasks like object detection, image segmentation, and facial recognition. While both fields leverage AI techniques, NLP primarily uses transformers like BERT, whereas computer vision often relies on convolutional neural networks (CNNs) and Vision Transformers (ViTs).
Where is the difference between NLP and computer vision?
- Getting Started with Milvus
- Retrieval Augmented Generation (RAG) 101
- Evaluating Your RAG Applications: Methods and Metrics
- Mastering Audio AI
- GenAI Ecosystem
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
How does zero-shot learning handle unseen classes?
Zero-shot learning (ZSL) is a technique used in machine learning where models can make predictions about classes they ha
How do I use cross-validation with a dataset?
Cross-validation is a statistical method used to evaluate the performance of a model on a dataset by dividing it into mu
What role does cosine similarity play in recommender systems?
Cosine similarity is a key technique used in recommender systems to measure how similar two items or users are based on