Ementorhub

What you'll learn

Describe text classification and related terminology (e.g., supervised machine learning)

Apply text classification to marketing data through a peer-graded project

Apply text classification to a variety of popular marketing use cases via structured homeworks

Train, evaluate and improve the performance of the text classification models you create for your final project

Skills you'll gain

Supervised Learning

Machine Learning

Google Cloud Platform

Natural Language Processing

Artificial Neural Networks

Marketing Analytics

Python Programming

Deep Learning

Machine Learning Algorithms

Performance Metric

Marketing

Tensorflow

Text Mining

Scikit Learn (Machine Learning Library)

There are 4 modules in this course

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. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Neural Networks and Deep Learning

Getting Started with Google Colab and Deep Learning

Linear Models and Classification Metrics