Neural networks are essential in machine learning because they excel at solving complex problems where traditional algorithms struggle. They are capable of learning hierarchical representations from raw data, making them highly effective for unstructured data such as images, text, and audio. Unlike rule-based systems, neural networks can generalize from examples, enabling tasks like image recognition, language translation, and speech processing. Their flexibility and scalability allow them to adapt to a wide range of applications, from predicting stock prices to autonomous driving.
Why do we even need neural networks in machine learning?
- AI & Machine Learning
- Natural Language Processing (NLP) Basics
- Master Video AI
- Retrieval Augmented Generation (RAG) 101
- Optimizing Your RAG Applications: Strategies and Methods
- 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 do geospatial analytics help businesses?
Geospatial analytics can significantly help businesses by enabling them to make informed decisions based on location-bas
How can TTS be used in interactive voice response (IVR) systems?
Text-to-speech (TTS) enhances interactive voice response (IVR) systems by enabling dynamic, real-time communication with
Why is disaster recovery important for businesses?
Disaster recovery is essential for businesses because it ensures they can quickly restore operations after unexpected ev