Word Embeddings Explained
🔥 Simple explanation of Word Embeddings. Words are represented as n-dimensional dense vectors. Beauty of Word Embeddings is in the way it manages to retain the semantic relationship among words, as every token has n-dimensional parameters explaining its characteristics.
Happy learning :)
🔥 Sections:
00:00 Introduction
00:29 Limitations of One-hot Encoding
02:09 Word Embeddings are powerful!!
03.26 Real-world Application
🔥 Resources:
Sentiment Analysis with Deep Neural Networks - using Word Embeddings: • Sentiment Analysis with LSTM | Deep L...
Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask):
1. Model Building: • Sentiment Analysis Machine Learning P... (Part-1)
2. Model Deployment: • PIP + Virtual Environment | Flask Dep... (Part-2)
Sentiment Analysis Project using Traditional ML: • Sentiment Analysis Project using Mach...
Our other popular ML Projects:
1. Analytics-enabled Marketing: • Marketing Analytics Project using Mac...
2. Credit Scoring Project: • Credit Scoring Project using Machine ...
3. Face Recognition Project: • Face Detection Machine Learning Proje...
🔥 Do like, share & subscribe to our channel. Keep in touch:
Website: https://www.skillcate.com
Email: [email protected]
Facebook: / mlprojects
Telegram: https://t.me/skillcate
Смотрите видео Word Embeddings Explained онлайн без регистрации, длительностью часов минут секунд в хорошем качестве. Это видео добавил пользователь Skillcate AI 29 Июль 2022, не забудьте поделиться им ссылкой с друзьями и знакомыми, на нашем сайте его посмотрели 1,866 раз и оно понравилось 29 людям.