Machine learning is a branch of artificial intelligence (AI) that focuses on building systems that can learn from data. It's a field that has seen rapid growth and is now widely used in various industries.
Key Concepts
- Supervised Learning: A type of machine learning where a model is trained on labeled data. The goal is to learn a mapping from inputs to outputs.
- Unsupervised Learning: A type of machine learning where a model is trained on unlabeled data. The goal is to find patterns and structures in the data.
- Reinforcement Learning: A type of machine learning where a model learns to make decisions by interacting with an environment.
Applications
Machine learning is used in a wide range of applications, including:
- Image Recognition: Used in applications like facial recognition and object detection.
- Natural Language Processing: Used in applications like chatbots and language translation.
- Recommendation Systems: Used in applications like movie and product recommendations.
Resources
For more information on machine learning, you can visit our Machine Learning Tutorial.
Learning Path
- Introduction to Machine Learning
- Supervised Learning Techniques
- Unsupervised Learning Techniques
- Reinforcement Learning Techniques
Machine Learning