Machine Learning (ML) is a subset of artificial intelligence (AI) that focuses on the development of computer systems that can learn and improve from experience without being explicitly programmed. Here are some key areas and tutorials that can help you delve into the world of machine learning.
Key Areas in Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Natural Language Processing (NLP)
- Computer Vision
Tutorials
Supervised Learning
Supervised learning is where you have a labeled dataset to train your model. Here's a basic tutorial on how to get started with it.
Unsupervised Learning
Unsupervised learning deals with finding patterns and information from data sets that are not labeled. This tutorial provides a good foundation.
Reinforcement Learning
Reinforcement learning is a type of machine learning where an agent learns to make decisions by performing actions and receiving rewards or penalties.
Natural Language Processing (NLP)
NLP focuses on the interaction between computers and humans through natural language. This tutorial covers the basics.
Computer Vision
Computer vision is the field of AI that trains computers to interpret and understand the visual world.
Remember, machine learning is a vast field, and there's always more to learn. For further reading, check out our comprehensive Machine Learning Resources.
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