University of Colorado Boulder - Unsupervised Text Classification for Marketing Analytics
- Offered byCoursera
Unsupervised Text Classification for Marketing Analytics at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Unsupervised Text Classification for Marketing Analytics at Coursera Highlights
- Earn a Certificate upon completion
Unsupervised Text Classification for Marketing Analytics at Coursera Course details
- Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within
- In this course, learners use unsupervised deep learning to train algorithms to extract topics and insights from text data
- Learners walk through a conceptual overview of unsupervised machine learning and dive into real-world datasets through instructor-led tutorials in Python
- This course uses Jupyter Notebooks and the coding environment Google Colab, a browser-based Jupyter notebook environment
- This course can be taken for academic credit as part of CU Boulder's Master of Science in Data Science (MS-DS) degree offered on the Coursera platform
Unsupervised Text Classification for Marketing Analytics at Coursera Curriculum
What is topic modeling?
Topic Modeling Lecture 1
Welcome and Where to Find Help
Introduction to Using Google Colab for this Course
Dr. Vargo's Topic Modeling Approach to YikYak Data
The Assumptions of a Topic Model, Bag of Words, and Natural Language Processing
Topic Modeling Lecture 2
Topic Modeling Lecture 3
Dr. Vargo?s Chapter on How Topic Modeling Compares with Lexicon-based Approaches
Topic Modeling Quiz
Prepping Amazon Review Data
Topic Modeling Lecture 4
Topic Modeling Lecture 5
Lecture Notebook Links
Coding Lab 1: Segmenting Data
Lab 1 Quiz
Pre-Processing Text and Training a Topic Model
Topic Modeling Lecture 6
Topic Modeling Lecture 7
Lecture Notebook Links
Lab 2: Classification and Visualization
Topic Modeling Evaluation, Classification, and Neural Network Approaches
Topic Modeling Lecture 8
Topic Modeling Lecture 9
Topic Modeling Lecture 10
Lecture Notebook Links
Papers (1, 2, and 3) on Topic Modeling Fit Statistics
Lab 3: Topic Modeling with BERTopic
Unsupervised Text Classification for Marketing Analytics at Coursera Admission Process
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