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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 4
Graph Embeddings
Summary
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Concept Check
What is a common approach used for Graph Embeddings?
Random sampling
PageRank algorithm
Breadth-first search
Deep learning
Which technique can be used to represent nodes in Graph Embeddings?
Node2Vec
Binary search
Heapsort
Merge sort
What is the goal of Graph Embeddings?
To capture graph structure
To count the number of edges
To perform matrix multiplication
To sort nodes alphabetically
Which type of information can Graph Embeddings capture?
Historical events
Structural and semantic information
Weather data
Geographical coordinates
How can Graph Embeddings be trained?
Using machine learning algorithms
Repeating a mantra
Using a compass and map
Manually inputting data
Check Answer
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Image Embeddings