Welcome to the Unsupervised Learning and Its Applications in Marketing course! In this course, you will delve into the fascinating world of unsupervised machine learning and its relevance to the field of marketing. Unsupervised learning is a powerful approach that allows us to uncover hidden patterns and insights from vast amounts of historical data without the need for explicit labels or human intervention. Through hands-on exercises and real-world examples, you will learn how to leverage the Python programming language to apply unsupervised learning algorithms in marketing contexts. Throughout the course, you will explore various unsupervised learning techniques, such as clustering, dimensionality reduction, and association rule mining. These techniques will enable you to identify customer segments, uncover meaningful relationships between variables, and gain valuable insights into consumer behavior. By mastering the applications of unsupervised learning in marketing, you will acquire the skills to extract actionable knowledge from data, make data-driven decisions, and unlock new opportunities for your marketing strategies. So, get ready to embark on a journey of discovery and innovation as you explore the fascinating world of unsupervised learning and its transformative applications in marketing. Let's dive in and unlock the hidden potential of data-driven marketing together! To succeed in this course, you should have a basic understanding of Python. You will also need certain software requirements, including Anaconda navigator.
Course Wrap-up
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Skills You'll Learn
K-Means Clustering, Dimensionality Reduction, Anomaly Detection, Association Learning, Unsupervised Learning
From the lesson
Weekly Summative Assessment: Semi-Supervised Learning聽and Recommender systems Using RBM
This assessment is a graded quiz based on the modules covered this week.
Taught By
Ambica Ghai