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Computer Science
Artificial Intelligence
Introduction to Artificial Intelligence
1. Foundations of Artificial Intelligence
2. Problem Solving and Search
3. Knowledge Representation and Reasoning
4. Machine Learning Fundamentals
5. Neural Networks and Deep Learning
6. Natural Language Processing
7. Computer Vision and Perception
8. AI Ethics and Societal Impact
6.
Natural Language Processing
6.1.
Text Preprocessing
6.1.1.
Tokenization
6.1.1.1.
Word Tokenization
6.1.1.2.
Sentence Tokenization
6.1.1.3.
Subword Tokenization
6.1.2.
Text Normalization
6.1.2.1.
Case Folding
6.1.2.2.
Stemming
6.1.2.3.
Lemmatization
6.1.2.4.
Stop Word Removal
6.1.3.
Text Representation
6.1.3.1.
Bag of Words
6.1.3.2.
TF-IDF
6.1.3.3.
N-gram Models
6.1.3.4.
Word Embeddings
6.2.
Language Modeling
6.2.1.
Statistical Language Models
6.2.1.1.
N-gram Models
6.2.1.2.
Smoothing Techniques
6.2.1.3.
Perplexity Evaluation
6.2.2.
Neural Language Models
6.2.2.1.
Feedforward Neural LM
6.2.2.2.
Recurrent Neural LM
6.2.2.3.
Transformer Language Models
6.2.3.
Word Embeddings
6.2.3.1.
Word2Vec
6.2.3.2.
GloVe
6.2.3.3.
FastText
6.2.3.4.
Contextual Embeddings
6.3.
Syntactic Processing
6.3.1.
Part-of-Speech Tagging
6.3.1.1.
Tag Sets
6.3.1.2.
Rule-Based Tagging
6.3.1.3.
Statistical Tagging
6.3.1.4.
Neural Tagging
6.3.2.
Parsing
6.3.2.1.
Context-Free Grammars
6.3.2.2.
Constituency Parsing
6.3.2.3.
Dependency Parsing
6.3.2.4.
Neural Parsing
6.3.3.
Chunking and Named Entity Recognition
6.3.3.1.
Phrase Chunking
6.3.3.2.
Named Entity Types
6.3.3.3.
Sequence Labeling
6.3.3.4.
Evaluation Metrics
6.4.
Semantic Processing
6.4.1.
Word Sense Disambiguation
6.4.1.1.
Sense Inventories
6.4.1.2.
Supervised WSD
6.4.1.3.
Knowledge-Based WSD
6.4.2.
Semantic Role Labeling
6.4.2.1.
PropBank and FrameNet
6.4.2.2.
Argument Identification
6.4.2.3.
Role Classification
6.4.3.
Coreference Resolution
6.4.3.1.
Anaphora Resolution
6.4.3.2.
Entity Linking
6.4.3.3.
Evaluation Metrics
6.5.
NLP Applications
6.5.1.
Information Extraction
6.5.1.1.
Relation Extraction
6.5.1.2.
Event Extraction
6.5.1.3.
Template Filling
6.5.2.
Text Classification
6.5.2.1.
Document Classification
6.5.2.2.
Sentiment Analysis
6.5.2.3.
Spam Detection
6.5.3.
Machine Translation
6.5.3.1.
Statistical MT
6.5.3.2.
Neural MT
6.5.3.3.
Evaluation Metrics
6.5.4.
Question Answering
6.5.4.1.
Reading Comprehension
6.5.4.2.
Knowledge-Based QA
6.5.4.3.
Open-Domain QA
6.5.5.
Text Summarization
6.5.5.1.
Extractive Summarization
6.5.5.2.
Abstractive Summarization
6.5.5.3.
Evaluation Methods
6.5.6.
Dialogue Systems
6.5.6.1.
Task-Oriented Dialogue
6.5.6.2.
Chatbots
6.5.6.3.
Conversational AI
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5. Neural Networks and Deep Learning
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7. Computer Vision and Perception