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Unsupervised Text Classification for Marketing Analytics

Курс от University of Colorado Boulder

Средний≈ 13.5 чАнглийский

О курсе

Discover patterns in marketing text without predefined outcome labels by combining topic modeling with text-derived network analysis. Learners build and inspect TF-IDF representations, select topic counts and membership assumptions, evaluate and interpret topic solutions, and construct directed or weighted networks from word co-occurrences and user mentions to identify central and bridging structures.

Навыки, которые вы освоите

Unsupervised Learning JSON Natural Language Processing Unstructured Data Text Mining Machine Learning Model Training Data Processing Deep Learning Model Evaluation Data Preprocessing Python Programming Marketing Analytics

Программа курса

5 модулей · 31 учебных материалов

01What is topic modeling?9 материалов

Introduction

Course Updates and Accessibility SupportЧтение Earn Academic Credit for your Work!Чтение Course SupportЧтение Introduce Yourself!Обсуждение

Lectures

Учитесь у экспертов

Chris J. Vargo

Associate Professor

Scott Bradley

Senior Engineer

Unsupervised Text Classification for Marketing Analytics

О курсе

Навыки, которые вы освоите

Программа курса

Introduction

Lectures

Учитесь у экспертов

Chris J. Vargo

Scott Bradley

Reference Docs

Assessments

Lectures

Reference Docs

Assessments

Lectures

Lecture Notebooks

Assessments

Lectures

Lecture Notebooks

Assessments

Lectures

Lecture Notebooks

Reference Docs

Assessments