Difference between revisions of "Word2Vec"
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[http://www.youtube.com/results?search_query=Word2Vec+word+vectors+nlp+nli+natural+language+semantics Youtube search...] | [http://www.youtube.com/results?search_query=Word2Vec+word+vectors+nlp+nli+natural+language+semantics Youtube search...] | ||
Revision as of 00:30, 19 September 2023
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 ... (GPT-4) ... GPT-5 ... 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.
