Machine Learning

10.
Advanced Topics and Specialized Areas
10.1.
Natural Language Processing
10.1.2.
Text Representation
10.1.2.1.
Bag of Words
10.1.2.1.1.
Term Frequency
10.1.2.1.3.
Limitations
10.1.2.3.
N-grams
10.1.2.3.3.
Skip-grams
10.1.2.4.
Word Embeddings
10.1.2.4.1.
Word2Vec
10.1.2.4.1.1.
Skip-gram Model
10.1.2.4.1.4.
Negative Sampling
10.1.2.4.2.
GloVe
10.1.2.4.2.1.
Global Vectors
10.1.2.4.2.3.
Factorization
10.1.2.4.3.
FastText
10.1.2.4.3.1.
Subword Information
10.1.3.
Language Models
10.1.3.3.
Transformer-Based Models
10.1.3.3.1.
BERT
10.1.3.3.2.
GPT
10.1.3.3.3.
T5
10.1.3.3.4.
RoBERTa
10.2.
Computer Vision
10.2.2.
Feature Extraction
10.2.2.1.
Traditional Methods
10.2.2.1.1.
SIFT
10.2.2.1.2.
SURF
10.2.2.1.3.
HOG
10.2.2.1.4.
LBP

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11. Machine Learning Operations and Deployment