Sentiment Analysis with NLP using Python and Flask
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
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
Audience and starting point
Selected published requirements: “Basics of Python programming”. See the provider page for the full requirements and current tool terms
Access and subscriptions
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
An original example for comparing learning plans. Ask whether the course teaches this task, includes practice and offers feedback; the diagram does not describe a provider’s course.
Marketing text-mining curriculum applies sentiment, topic modeling, NLP, named-entity recognition, classification, topic clustering and predictive analysis to customer reviews, social posts, feedback and news. Named uses include…
12 modules and 36 assignments. Coursera estimates two weeks at ten hours per week. The public outline does not establish coding or learner-built modelsCheck current priceAsk about teaching language
Learn sentiment workflow and RNN/LSTM concepts, then implement LSTM sentiment modeling in Keras, the source names voice-of-customer reviews/surveys/social material as marketing/service applications
7 sections • 19 lectures • 2h 48m total lengthCheck current priceEnglish
