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AI generations
Unit 1
Langchain
Introduction to Langchain
Applications of Langchain in AI Generations
Langchain and Natural Language Processing
Langchain and Neural Networks
Unit 2
Retrieval Augmented Generations
Introduction to Retrieval Augmented Generations
Retrieval Techniques in AI Generation
Applications of Retrieval Augmented Generations
Unit 3
Vector Embeddings
Introduction to Vector Embeddings
Word Embeddings
Image Embeddings
Graph Embeddings
Unit 3 • Chapter 2
Word Embeddings
Summary
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Concept Check
What is an important concept in natural language processing?
Machine Learning
Word Embeddings
Deep Learning
Neural Networks
Why are Word Embeddings important in NLP?
To represent words as vectors
To generate images
To classify documents
To predict stock prices
How are Word Embeddings created?
By manual annotation
By using predefined rules
By visual inspection
By learning from large text corpora
What is the purpose of Word Embeddings?
To count word occurrences
To capture semantic relationships between words
To correct spelling mistakes
To remove stopwords
Which technique is commonly used to create Word Embeddings?
Decision Trees
Random Forests
Support Vector Machines
Word2Vec
Check Answer
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Introduction to Vector Embeddings
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Image Embeddings