04 - Specialized Domains Index

Specialized Domains

Overview

Deep diving into specific application areas of AI. Master domain-specific techniques, models, and best practices.

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Computer Vision

Fundamentals

• Computer Vision Overview
• Image Preprocessing
• Image Augmentation
• Color Spaces
• Image Filtering
• Edge Detection

Object Detection

• Object Detection Overview
• YOLO (You Only Look Once)
• R-CNN Family
• SSD (Single Shot Detector)
• RetinaNet
• Non-Maximum Suppression
• Anchor Boxes

Image Segmentation

• Semantic Segmentation
• Instance Segmentation
• Panoptic Segmentation
• U-Net
• Mask R-CNN
• DeepLab

Image Classification

• Image Classification Fundamentals
• Transfer Learning in CV
• Data Augmentation for Images
• Few-Shot Learning in CV

Video Analysis

• Video Understanding
• Temporal CNNs
• 3D CNNs
• Optical Flow
• Action Recognition
• Video Segmentation

Generative Models

• GANs for Images
• StyleGAN
• CycleGAN
• Diffusion Models for Images
• Stable Diffusion
• DALL-E
• Image-to-Image Translation

OCR & Document AI

• Optical Character Recognition
• Text Detection in Images
• Document Layout Analysis
• Tesseract OCR

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Natural Language Processing

Text Preprocessing

• Text Preprocessing Techniques
• Tokenization
• Stemming and Lemmatization
• Stop Words Removal
• Text Normalization

Word Embeddings

• Word Embeddings Overview
• Word2Vec
• GloVe
• FastText
• Contextual Embeddings
• Sentence Embeddings

Language Models

• Language Modeling Fundamentals
• N-gram Models
• RNN Language Models
• Transformer Language Models
• Masked Language Modeling
• Causal Language Modeling

Named Entity Recognition

• NER Fundamentals
• CRF (Conditional Random Fields)
• BiLSTM-CRF
• Transformer-based NER
• Entity Linking

Information Extraction

• Relation Extraction
• Event Extraction
• Knowledge Graph Construction
• Coreference Resolution

Text Classification

• Text Classification Methods
• Sentiment Analysis
• Topic Modeling
• Intent Classification
• Emotion Detection

Sequence-to-Sequence

• Seq2Seq Models
• Machine Translation
• Text Summarization
• Question Answering
• Dialogue Systems

Semantic Search

• Semantic Search Fundamentals
• Dense Retrieval
• Bi-Encoders
• Cross-Encoders
• Hybrid Search Methods

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Ethics & Responsible AI

Bias & Fairness

• Bias in ML Systems
• Fairness Metrics
• Demographic Parity
• Equalized Odds
• Bias Mitigation Techniques
• Fair Representation Learning

Model Interpretability

• Interpretability vs Explainability
• Feature Importance
• SHAP Values
• LIME
• Attention Visualization
• Saliency Maps
• Integrated Gradients

Transparency

• Model Transparency
• Black Box vs White Box Models
• Model Cards
• Data Cards
• Documentation Best Practices

Security

• Adversarial Examples
• Model Robustness
• Adversarial Training
• Model Stealing
• Data Poisoning
• Backdoor Attacks

Privacy

• Privacy in ML
• Membership Inference Attacks
• Model Inversion
• Privacy-Preserving Techniques

Regulatory Compliance

• AI Regulations Overview
• GDPR for AI
• EU AI Act
• Algorithmic Accountability
• Right to Explanation

Societal Impact

• AI Safety
• Alignment Problem
• Value Alignment
• AI Ethics Frameworks
• Sustainability in AI
• Environmental Impact of AI

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Progress Tracking

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SORT file.name ASC

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