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Java Deep Learning Projects

You're reading from  Java Deep Learning Projects

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997454
Pages 436 pages
Edition 1st Edition
Languages
Toc

Table of Contents (13) Chapters close

Preface 1. Getting Started with Deep Learning 2. Cancer Types Prediction Using Recurrent Type Networks 3. Multi-Label Image Classification Using Convolutional Neural Networks 4. Sentiment Analysis Using Word2Vec and LSTM Network 5. Transfer Learning for Image Classification 6. Real-Time Object Detection using YOLO, JavaCV, and DL4J 7. Stock Price Prediction Using LSTM Network 8. Distributed Deep Learning – Video Classification Using Convolutional LSTM Networks 9. Playing GridWorld Game Using Deep Reinforcement Learning 10. Developing Movie Recommendation Systems Using Factorization Machines 11. Discussion, Current Trends, and Outlook 12. Other Books You May Enjoy

Using Word2Vec for neural word embeddings

Word2Vec is a two-layer neural network that processes texts and turns them into numerical features. This way, the output of the Word2Vec is a vocabulary in which each word is embedded in vector space. The resulting vector can then be fed into a neural network for better understanding of natural languages. The novelist EL Doctorow has expressed this idea quite poetically in his book Billy Bathgate:

"It's like numbers are language, like all the letters in the language are turned into numbers, and so it's something that everyone understands the same way. You lose the sounds of the letters and whether they click or pop or touch the palate, or go ooh or aah, and anything that can be misread or con you with its music or the pictures it puts in your mind, all of that is gone, along with the accent, and you have a new understanding...
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