Machine learning enables systems to learn patterns and make decisions from data without being explicitly programmed. This learning process allows machines to adapt to new situations, improve over time, and automate tasks. For example, a machine learning model can classify emails as spam or non-spam by recognizing patterns in the content. Machines learn to provide solutions to problems that are too complex for rule-based systems, such as natural language understanding, image recognition, and predictive analytics, making them valuable in diverse industries.
Why does machine learn?
- Retrieval Augmented Generation (RAG) 101
- Evaluating Your RAG Applications: Methods and Metrics
- Large Language Models (LLMs) 101
- Exploring Vector Database Use Cases
- The Definitive Guide to Building RAG Apps with LlamaIndex
- 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
Is computer vision all about deep learning now?
While deep learning has become a dominant force in computer vision, it is not the sole approach used in the field. Deep
How are LLMs optimized for performance?
LLMs are optimized for performance using techniques like parameter pruning, model quantization, and efficient training a
What is the importance of data integrity in analytics?
Data integrity is vital in analytics because it ensures the accuracy, consistency, and reliability of the data being ana