Difference between revisions of "Word2Vec"
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* [[Embedding]] ... [[Fine-tuning]] ... [[Retrieval-Augmented Generation (RAG)|RAG]] ... [[Agents#AI-Powered Search|Search]] ... [[Clustering]] ... [[Recommendation]] ... [[Anomaly Detection]] ... [[Classification]] ... [[Dimensional Reduction]]. [[...find outliers]] | * [[Embedding]] ... [[Fine-tuning]] ... [[Retrieval-Augmented Generation (RAG)|RAG]] ... [[Agents#AI-Powered Search|Search]] ... [[Clustering]] ... [[Recommendation]] ... [[Anomaly Detection]] ... [[Classification]] ... [[Dimensional Reduction]]. [[...find outliers]] | ||
| − | * [[Large Language Model (LLM)]] ... [[Large Language Model (LLM)#Multimodal|Multimodal]] ... [[Foundation Models (FM)]] ... [[Generative Pre-trained Transformer (GPT)|Generative Pre-trained]] ... [[Transformer | + | * [[Large Language Model (LLM)]] ... [[Large Language Model (LLM)#Multimodal|Multimodal]] ... [[Foundation Models (FM)]] ... [[Generative Pre-trained Transformer (GPT)|Generative Pre-trained]] ... [[Transformer]] ... [[Attention]] ... [[Generative Adversarial Network (GAN)|GAN]] ... [[Bidirectional Encoder Representations from Transformers (BERT)|BERT]] |
* [[Doc2Vec]] | * [[Doc2Vec]] | ||
* [[Node2Vec]] | * [[Node2Vec]] | ||
Latest revision as of 09:39, 28 May 2025
Youtube search... ...Google search
- Embedding ... Fine-tuning ... RAG ... Search ... Clustering ... Recommendation ... Anomaly Detection ... Classification ... Dimensional Reduction. ...find outliers
- Large Language Model (LLM) ... Multimodal ... Foundation Models (FM) ... Generative Pre-trained ... Transformer ... Attention ... GAN ... BERT
- Doc2Vec
- Node2Vec
- Skip-Gram
- Global Vectors for Word Representation (GloVe)
- Bag-of-Words (BoW)
- Continuous Bag-of-Words (CBoW)
- Similarity
- TensorFlow
- Embedding ... Fine-tuning ... RAG ... Search ... Clustering ... Recommendation ... Anomaly Detection ... Classification ... Dimensional Reduction. ...find outliers
- Introduction to Word Embedding and Word2Vec | Dhruvil Karani - Towards Data Science - Medium
- Distributed Representations of Words and Phrases and their Compositionality | Tomas Mikolov - Google
a shallow, two-layer neural networks which is trained to reconstruct linguistic contexts of words. It takes as its input a large corpus of words and produces a vector space, typically of several hundred dimensions, with each unique word in the corpus being assigned a corresponding vector in the space.
