Deepfakes and Fake News Detection

  1. Core Technologies for Synthetic Media Generation
    1. Generative Models Overview
      1. Generative vs. Discriminative Models
        1. Model Objectives and Applications
          1. Training Paradigms
            1. Evaluation Metrics
            2. The Role of Deep Learning
              1. Neural Networks in Media Synthesis
                1. Training Data Requirements and Quality
                  1. Computational Resources and Scalability
                  2. Latent Space Representation
                    1. Concept of Latent Variables
                      1. Dimensionality and Interpretability
                        1. Manipulating Latent Space for Generation
                      2. Generative Adversarial Networks
                        1. Core Architecture and Principles
                          1. The Generator Network
                            1. Function and Design Principles
                              1. Architecture Variations
                                1. Output Quality Control
                                2. The Discriminator Network
                                  1. Function and Design Principles
                                    1. Binary Classification Task
                                      1. Feature Learning
                                    2. The Adversarial Training Process
                                      1. Game Theory Foundations
                                        1. Loss Functions and Objectives
                                          1. Training Dynamics and Convergence
                                            1. Mode Collapse and Training Instability
                                            2. GAN Architectures and Variants
                                              1. Deep Convolutional GAN
                                                1. Structure and Implementation
                                                  1. Applications in Image Generation
                                                    1. Training Considerations
                                                    2. StyleGAN and Variants
                                                      1. Style Transfer Mechanisms
                                                        1. High-Fidelity Synthesis
                                                          1. Controllable Generation
                                                          2. CycleGAN
                                                            1. Unpaired Image-to-Image Translation
                                                              1. Cycle Consistency Loss
                                                                1. Domain Adaptation
                                                                2. Conditional GANs
                                                                  1. Class-Conditional Generation
                                                                    1. Text-to-Image Synthesis
                                                                      1. Controllable Attributes
                                                                      2. Progressive GANs
                                                                        1. Multi-Scale Training
                                                                          1. Quality Improvement Strategies
                                                                            1. Computational Efficiency
                                                                        2. Autoencoders and Variational Models
                                                                          1. Basic Autoencoder Structure
                                                                            1. Encoder Architecture
                                                                              1. Feature Extraction and Compression
                                                                                1. Bottleneck Representation
                                                                                  1. Dimensionality Reduction
                                                                                  2. Decoder Architecture
                                                                                    1. Reconstruction Process
                                                                                      1. Information Recovery
                                                                                        1. Quality Assessment
                                                                                      2. Variational Autoencoders
                                                                                        1. Probabilistic Modeling Approach
                                                                                          1. Latent Variable Inference
                                                                                            1. Applications in Media Synthesis
                                                                                              1. Comparison with GANs
                                                                                            2. Transformer Models and Large Language Models
                                                                                              1. Transformer Architecture
                                                                                                1. Encoder-Decoder Structure
                                                                                                  1. Multi-Head Attention Mechanisms
                                                                                                    1. Positional Encoding
                                                                                                      1. Layer Normalization and Residual Connections
                                                                                                      2. Self-Attention Mechanisms
                                                                                                        1. Attention Scores and Context
                                                                                                          1. Query-Key-Value Framework
                                                                                                            1. Computational Complexity
                                                                                                            2. Applications in Text Generation
                                                                                                              1. Language Modeling Tasks
                                                                                                                1. Text Completion and Paraphrasing
                                                                                                                  1. Creative Writing and Summarization
                                                                                                                  2. Applications in Visual Media
                                                                                                                    1. Vision Transformers
                                                                                                                      1. Multimodal Transformers
                                                                                                                        1. Text-to-Image Generation
                                                                                                                      2. Diffusion Models
                                                                                                                        1. Denoising Diffusion Process
                                                                                                                          1. Forward and Reverse Processes
                                                                                                                            1. Noise Scheduling
                                                                                                                              1. Training Objectives
                                                                                                                              2. Applications in Image Generation
                                                                                                                                1. High-Quality Image Synthesis
                                                                                                                                  1. Controllable Generation
                                                                                                                                    1. Inpainting and Editing
                                                                                                                                    2. Comparison with Other Generative Models
                                                                                                                                      1. Quality vs. Speed Trade-offs
                                                                                                                                        1. Training Stability
                                                                                                                                          1. Controllability Features

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                                                                                                                                      2. Foundations of Machine Learning for Media Analysis

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                                                                                                                                      4. Fake News Detection: Text-Based Analysis