Related skills · check the marketing fit
Implement a concise Keras/Python sentiment engine, develop the case-study model and extend it with CNNs, source targets understanding opinions about company products/services
Dr. Mohammad Nauman · Udemy
Implement a concise Keras/Python sentiment engine, develop the case-study model and extend it with CNNs. Source targets understanding opinions about company products/services
Selected published requirements: “Basic understanding of the Python language”. 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.
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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
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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