Marketing focus
Clean customer reviews/tweets, analyze rating/sentiment correlation and positive/negative keywords, and compare TextBlob/EmoLex/VADER/NRCLex/BERT/Naive Bayes outputs, explicit customer/social datasets
Christ Raharja · Udemy
Clean customer reviews/tweets, analyze rating/sentiment correlation and positive/negative keywords, and compare TextBlob/EmoLex/VADER/NRCLex/BERT/Naive Bayes outputs. Explicit customer/social datasets
Selected published requirements: “No previous experience in sentiment analysis is required”. “Basic knowledge in Python and NLP”. See the provider page for the full requirements and current tool terms
Recorded Udemy course advertised with a public course preview. Exact lesson count may be unknown. Purchase or organization-subscription terms and current availability require checking
Related tasks, tools and formats. Check the differences before choosing.
Meta Brains , Skool of AI
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Use TextBlob to classify text sentiment and build a Flask interface, public description explicitly frames customer reviews/social opinions as applications. A technical NLP course transfers to feedback monitoring
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Build a positive/negative review classifier in a ten-lesson/79-minute project after Python/NumPy/pandas/ML/TensorFlow foundations, the whole course counts once and is adjacent technical training