Doc2vec_cnn_rnn
This program also does sentiment analysis on IMDB movie reviews, but the reviews are first preprocessed with gensim's Doc2Vec that takes each review and converts the words to vectors. The vectorized words are then inputted into a CNN to find invariant features, followed by an RNN to learn the states. Accuracy after ten iterations with each word represented by a 128-length vector was 90.09%.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Word Embeddings And Document Vectors | 25 | 5 years ago | 1 | Python | ||||||
| An evaluation of word-embeddings for classification | ||||||||||
| Dataminingproject Whomadethatmovie | 6 | 11 years ago | Python | |||||||
| Data Mining project using IMDB, Movilens and Wikipedia datasets | ||||||||||
| Doc2vec_cnn_rnn | 6 | 7 years ago | Jupyter Notebook | |||||||
| This program also does sentiment analysis on IMDB movie reviews, but the reviews are first preprocessed with gensim's Doc2Vec that takes each review and converts the words to vectors. The vectorized words are then inputted into a CNN to find invariant features, followed by an RNN to learn the states. Accuracy after ten iterations with each word represented by a 128-length vector was 90.09%. | ||||||||||
| Deep_nlp_pydata | 5 | 6 years ago | mit | Jupyter Notebook | ||||||
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Jupyter Notebook
Vector
Recurrent Neural Networks
Sentiment
Sentiment Analysis
Word2vec
Imdb