Machine learning is a subset of artificial intelligence (AI) that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data. It’s a powerful technology with applications across various domains.
In machine learning, computers analyze and identify patterns in data, allowing them to make informed predictions or decisions without being explicitly programmed. This process involves training models on historical data to recognize patterns and relationships, which can then be applied to new, unseen data.
Machine learning is divided into supervised learning (where models are trained on labeled data), unsupervised learning (where models find patterns in unlabeled data), and reinforcement learning (where models learn through interaction with an environment).
Key techniques in machine learning include
- Regression (predicting numerical values)
- Classification (categorizing data into classes)
- Clustering (grouping similar data points)
- Neural networks (inspired by the human brain)
Machine learning has transformed industries such as healthcare, finance, and autonomous vehicles, and it continues to advance rapidly, with applications in natural language processing, computer vision, and more.