Most Benchmarked Datasets in Neural Sentiment Analysis With in PyTorch and TensorFlow

Most Benchmarked Datasets in Neural Sentiment Analysis With in PyTorch and TensorFlow

Sentiment analysis is a technique in natural language processing that deals with the order of assessments communicated in a bit of text. If you are still wondering about it then this article is for you. Let's explore it with us now.

With the expanding prominence of blogging sites, a massive number of clients share reviews on various parts of life consistently. Therefore popular sites like Amazon, Twitter are rich wellsprings of information for opinion mining and sentiment analysis.

Sentiment analysis is a technique in natural language processing that deals with the order of assessments communicated in a bit of text. In other words, it is used to check the polarity of the sentences. 

Sentiment analysis approach utilises an AI approach or a vocabulary based way to deal with investigating human sentiment about a point. The test for sentiment investigation lies in recognizing human feelings communicated in this content, for example, Twitter information.

Here, our focus will be to cover the details of some of the most popular datasets used in sentiment analysis. Further,we will focus on executing the code on these datasets using Tensorflow and Pytorch.

developers corner datasets natural language processing neural sentiment analysis opinion mining pytorch sentiment analysis

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Datasets in Neural Sentiment Analysis With Implementation in PyTorch and TensorFlow

Sentiment analysis is a technique in natural language processing that deals with the order of assessments communicated in a bit of text.

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