Chapter 9 - Modern Deep Learning#
Transformers#
Basic Architecture#
Encoder-Decoder Structure
Self-Attention Mechanism
Position Encoding
Feed-Forward Networks
Key Components#
Multi-Head Attention
Layer Normalization
Residual Connections
Output Generation
Popular Models#
BERT
GPT Series
T5
Implementation Examples
Attention Mechanisms#
Understanding Attention#
Basic Concept
Types of Attention
Importance Weighting
Context Learning
Implementation Details#
Query-Key-Value
Attention Scores
Softmax Application
Output Computation
Practical Applications#
Machine Translation
Text Summarization
Question Answering
Image Captioning
Generative AI Basics#
Types of Generation#
Text Generation
Image Generation
Audio Synthesis
Video Creation
Core Concepts#
Latent Space
Sampling Methods
Temperature Control
Beam Search
Popular Techniques#
Diffusion Models
GANs
Autoregressive Models
Hybrid Approaches
Model Deployment#
Deployment Preparation#
Model Optimization
Version Control
Documentation
Testing Strategies
Deployment Options#
Cloud Services
Edge Devices
Mobile Applications
Web Integration
Monitoring and Maintenance#
Performance Tracking
Error Handling
Updates and Versioning
Resource Management
Best Practices#
Model Development#
Architecture Selection
Hyperparameter Tuning
Training Strategies
Validation Methods
Production Considerations#
Scalability
Security
Cost Optimization
Maintenance
Ethical Considerations#
Bias Detection
Fairness Metrics
Privacy Concerns
Responsible AI