University of Colorado Boulder - Supervised Text Classification for Marketing Analytics
- Offered byCoursera
Supervised Text Classification for Marketing Analytics at Coursera Overview
Duration | 12 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Supervised Text Classification for Marketing Analytics at Coursera Highlights
- Reset flexible deadlines in accordance to your schedule
Earn a Certificate upon completion
Supervised Text Classification for Marketing Analytics at Coursera Course details
- In this course, students learn how to use supervised deep learning to train algorithms to tackle text classification tasks
- Students walk through a conceptual overview of supervised machine learning and dive into real-world datasets through instructor-led tutorials in Python
- The course concludes with a major project
- 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
Supervised Text Classification for Marketing Analytics at Coursera Curriculum
The Supervised Machine Learning Workflow
Specialization Introduction
Text Classification Lecture 1
Text Classification Lecture 2
Text Classification Lecture 5 (Repeated in Week 3)
Welcome and Where to Find Help
Introduction to using Google Colab for this course
Python Syntax Review
Neural Networks and Deep Learning
Text Classification Lecture 3
Text Classification Lecture 4
An Example Codebook from Dr. Vargo
An Example Paper from Dr. Vargo
Supervised Text Classification
Getting Started with Google Colab and Deep Learning
Text Classification Lecture 5
Text Classification Lecture 6
Lecture Notebook Links
Coding Lab 1: Data Preparation with Pandas
Lab 1 Quiz
Linear Models and Classification Metrics
Text Classification Lecture 7
Text Classification Lecture 8
Lecture Notebook Links
Coding Lab 2: Building a Model with K-Train
Lab 2 Quiz
Supervised Text Classification for Marketing Analytics at Coursera Admission Process
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