From the course: Agentic AI Fundamentals: Architectures, Frameworks, and Applications
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Machine learning for agents
From the course: Agentic AI Fundamentals: Architectures, Frameworks, and Applications
Machine learning for agents
- Machine learning is a result of applying algorithms to learn from data and make choices without being explicitly told to do so. If this sounds a lot like artificial intelligence, you're right. Because machine learning is a form of artificial intelligence and is the foundation for most AI systems. Essentially, ML is the theory and methodology. And agentic AI frameworks, which we'll cover in the next set of videos, are practical tools that bring the theory to life. Machine learning allows agents to learn from experiences independently. And it's been around and in use for years to solve practical business problems, such as spotting fraudulent applications and finding accounting anomalies. By training models with vast data sets to identify patterns, machine learning models equipped agents with the autonomy to make decisions without human oversight. Think of it kind of like training a classroom full of people using these different techniques. There are three main machine learning models…
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