Machine Learning (ML) is a branch of artificial intelligence that enables systems to learn patterns from data and improve their performance over time without being explicitly programmed. It focuses on building models that can make predictions, identify patterns, and support decision-making based on experience (data).
In data science and AI development, machine learning is used to analyze large datasets, automate tasks, and create intelligent systems that adapt to new inputs. The more data a model processes, the more accurate it can become.
For example:
- A recommendation system suggests movies or products based on user behavior.
- Email systems detect and filter spam messages automatically.
- A banking system identifies fraudulent transactions using pattern detection.
- A weather model predicts future conditions based on historical data.
Common types and concepts related to machine learning include:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Training Data & Test Data
- Algorithms (Decision Trees, SVM, Neural Networks)
- Feature Engineering
- Model Training
- Predictive Analytics
- Deep Learning
