Front-End Development Trends in 2025: What Every Developer Should Know
27 August 2025
Machine Learning vs Deep Learning: What’s the Difference?
Machine Learning (ML) and Deep Learning (DL) are often used interchangeably with AI, but they are not the same.
Machine Learning is a subset of AI where systems learn from data without being explicitly programmed. For example, spam filters that get better at detecting unwanted emails the more data they process.
Deep Learning is a subset of machine learning that uses neural networks with many layers (hence "deep") to process complex data. This is what powers image recognition, natural language processing (NLP), and speech-to-text tools.
Key Differences:
- ML works well with structured data and simpler tasks.
- DL is better at handling large, unstructured data like images, audio, and video.
- DL requires massive computational power compared to ML.
Both ML and DL are fundamental to today’s AI applications, but deep learning is what enables cutting-edge breakthroughs like ChatGPT and self-driving cars.
