Main Reference PaperTwitter sentiment analysis with deep convolutional neural networks, Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015 [python].
  • The word embeddings are initialized using word2vec. A sentiment analysis of tweets is performed for predicting polarities of phrase levels. The proposed deep convolutional neural network classifies the tweets into positive, negative and neutral classes.

Description
  • The word embeddings are initialized using word2vec. A sentiment analysis of tweets is performed for predicting polarities of phrase levels. The proposed deep convolutional neural network classifies the tweets into positive, negative and neutral classes.

  • To find word representations that are useful for predicting the surrounding words in a sentence or a document.

  • To compute the gradients that automatically tunes the learning rate.

Aim & Objectives
  • To find word representations that are useful for predicting the surrounding words in a sentence or a document.

  • To compute the gradients that automatically tunes the learning rate.

  • Training is processed by stochastic gradient descent (SGD) and back propagation algorithm is used to compute the gradients that automatically tunes the learning rate.

Contribution
  • Training is processed by stochastic gradient descent (SGD) and back propagation algorithm is used to compute the gradients that automatically tunes the learning rate.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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