Deep Neural Networks
(เครือข่ายประสาทเทียมเชิงลึก)
Definition
Deep Neural Networks (เครือข่ายประสาทเทียมเชิงลึก) Hard Skill
Deep Neural Networks are a class of machine learning models composed of multiple layers of interconnected nodes that simulate the human brain’s neural structure to recognize patterns and make decisions.
Expertise Level
Level 1
Basic
1. Understands the basic concept of neural networks and layers.
2. Can explain the function of neurons, activation functions, and basic forward propagation.
3. Familiar with common architectures like feedforward neural networks.
Level 2
Intermediate
1. Can build and train deep neural network models with multiple hidden layers.
2. Understands backpropagation and optimization algorithms like gradient descent.
3. Able to apply techniques such as dropout and batch normalization to improve training.
Level 3
Advanced
1. Expertise in designing and optimizing complex deep neural network architectures for specific tasks.
2. Can implement and customize advanced neural network variants like convolutional, recurrent, or transformer networks.
3. Able to troubleshoot and fine-tune models for maximum performance and generalization.
