Word Embeddings, Word2Vec And CBOW Indepth Intuition And Working- Part 1 | NLP For Machine Learning
29.4 هزار بار بازدید -
2 سال پیش
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Time stamps:
Time stamps:
00:00:00 Introduction To Word Embeddings
00:06:50 Word2vec Intuition
00:24:57 Word2vec CBOW Detailed Explanation
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#word2vec #wordembeddings
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Word embeddings are a type of natural language processing technique used to represent words in a numerical format, called a vector. The idea behind word embeddings is to capture the meaning of words based on the context in which they appear. This allows the model to understand the similarity and relationships between words, even if they have never seen them before.
Word2Vec is a popular method for creating word embeddings. It uses a neural network to learn the vector representation of words by predicting the surrounding context words given a target word. The neural network is trained on a large corpus of text, and the resulting word vectors are used to represent words in the corpus.
The resulting word vectors have several properties that make them useful for many natural language processing tasks, such as text classification, machine translation, and language modeling.
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00:00:00 Introduction To Word Embeddings
00:06:50 Word2vec Intuition
00:24:57 Word2vec CBOW Detailed Explanation
------------------------------------------------------------------------------------------
#word2vec #wordembeddings
Best Affordable Data Science Course From Pwskills(6-7 Months)
Impact Batch:- Data-Science-Masters (Full Stack Data Science)
1. Data Science Masters Hindi: https://bit.ly/3CKX1od (Hindi)
2. Data Science Masters English: https://bit.ly/3iEjWuH (English)
------------------------------------------------------------------------------------------------
Word embeddings are a type of natural language processing technique used to represent words in a numerical format, called a vector. The idea behind word embeddings is to capture the meaning of words based on the context in which they appear. This allows the model to understand the similarity and relationships between words, even if they have never seen them before.
Word2Vec is a popular method for creating word embeddings. It uses a neural network to learn the vector representation of words by predicting the surrounding context words given a target word. The neural network is trained on a large corpus of text, and the resulting word vectors are used to represent words in the corpus.
The resulting word vectors have several properties that make them useful for many natural language processing tasks, such as text classification, machine translation, and language modeling.
------------------------------------------------------------------------------------------------------------
Check Out My Other Playlist
Python Playlist:
Python In English:Complete Road Map To Be Expert In Pyt...
Python In Hindi: Tutorial 1- Python Overview in Hindi
Stats Playlist:
English 7 Days Statistics Live Session :Live Day 1- Introduction To statistic...
Hindi: Stats Playlist: Starter Roadmap For Learning Statisti...
Complete ML Playlist: Complete Road Map To Be Expert In Pyt...
Hindi: ML Playlist: Introduction To Machine Learning Algo...
5 DaysLive Deep Learning Playlist: 5 Days Live Deep Learning Community S...
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2 سال پیش
در تاریخ 1401/11/05 منتشر شده
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