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klotz: neural network* + nlp*

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11. Email Classification with Machine Learning and Word Embeddings for Improved Customer Support

    However it is interesting that LSTM can achieve good performance
    with word vectors based on a small corpus even though it scored terrible in the semantic and syntactic analysis.
    
    LSTM does perform better than the other classifiers, but it does require more data. If NLP tasks are to be solved in other domains that do not generate enough data for a LSTM to work properly it would be advisable to train a SVM using AvgWV. LSTM is more adaptable but knowing how to optimise the network does require domain knowledge and experience with gradient-decent classifiers.

    2018-12-28 Tags: email, classification, word2vec, nlp, machine learning, deep learning, neural network, text, swedish, glove, skipgram, cbow, . skipgram-ng by klotz
12. Word2Vec — a baby step in Deep Learning but a giant leap towards Natural Language Processing

    2018-07-24 Tags: word2vec, explanation, nlp, machine learning, neural networks by klotz
13. “Report on Text Classification using CNN, RNN & HAN”

    2018-07-18 Tags: nlp, deep learning, tutorial, cnn, rnn, han, neural network by klotz
14. [1408.5882] Convolutional Neural Networks for Sentence Classification

    2018-07-18 Tags: cnn, neural network, nlp, classification by klotz
15. Detecting Sarcasm with Deep Convolutional Neural Networks

    2018-06-22 Tags: sarcasm, sentiment, nlp, word2vec, rnn, neural network by klotz
16. Theory and Application with Convolutional Neural Networks

    Semi-Supervised Learning with Multi-View Embedding:
    Rie Johnson
    RJ Research Consulting
    Tarrytown, NY, USA
    Tong Zhang
    Baidu Inc., Beijing, China
    Rutgers University, Piscataway, NJ, USA

    2015-09-09 Tags: neural network, cnn, word, nlp by klotz

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