NLP in Python: Probability Models, Statistics, Text Analysis
Build a customer-review sentiment pipeline and ecommerce review analysis combining entity recognition/topic modeling, with probabilistic features/Naive Bayes and model deployment. Broader NLP foundations accompany the explicit…
Build a customer-review sentiment pipeline and ecommerce review analysis combining entity recognition/topic modeling, with probabilistic features/Naive Bayes and model deployment. Broader NLP foundations accompany the explicit commercial application
Audience and starting point
Selected published requirements: “Basic Python programming experience - familiarity with functions, loops, and data structures”. “No advanced Python knowledge required”. 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.
Shared topic: Customer analytics and personalization
O.P. Jindal Global University
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
