Crypto
dashboard
using
Sentiment analysis
extracting emotions through AI!
Sentiment analysis is extremely useful in social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics.
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NLP consists in studying how computer languages and human languages interact. We will use a Pyhton library called TextBlob and its module sentiment for analyzing the subjectivity or polarity of a text. The base of this model are statistics.
Contrary to Supervised Machine Learning, Unsupervised Learning corresponds to situations in which we do not have a target variable that we are trying to predict, but we hypothesize that the data we have can be compared within groups. K-Means method is a partitioning technique that separates observations into K-groups, where each observation is considered to belong to the group where the mean is the closest according to a given distance.
Recurrent neural networks are a family of layers that can take into
account the sequential nature of input data. Recurrent networks have
shown impressive results and helped developping the field of NLP.
But they are far from perfect.
Thanks to state-of-the-art
new methods like attention layers, we change the way sequential data
is processed by neural networks letting us to have better results.
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