Chapter 2: AI Terms and Concepts
Learning Objectives
Understand supervised vs. unsupervised learning
Understand steps in machine learning
Understand neural networks
Supervised vs. Unsupervised Learning
There are two main types of machine learning techniques:
- Supervised Learning: Uses labeled data for training
- Unsupervised Learning: Works with unlabeled data to find patterns
Understanding the difference is crucial for choosing the right approach for your AI project.
Watch and Learn
Steps in Machine Learning
The process of machine learning can be broken down into several key steps:
- Collecting Data
- Preparing Data
- Choosing a Model
- Training the Model
- Evaluating the Model
- Fine-tuning
Each step is crucial for developing an effective machine learning model.
Practice Exercise
Create a flowchart illustrating the machine learning steps. Explain how each step contributes to the overall process.
Neural Networks
Neural Networks are a fundamental concept in modern AI, inspired by the human brain's structure:
- Composed of interconnected nodes (neurons)
- Organized in layers (input, hidden, output)
- Learn by adjusting connections between neurons
Understanding neural networks is key to grasping how deep learning models process information and make decisions.