Supervised/unsupervised Machine Learning Projects
Published 7/2025
Created by Aaron Sanchez
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 28 Lectures ( 8h 58m ) | Size: 8.44 GB
Real-World Projects Based on Clients and Products
What you'll learn
Housing Valuation
Customer Churn
Customer Segmentation
Product Recommender
Requirements
Python
Data Science
Description
This course is a compilation of both Supervised and Unsupervised Machine Learning courses:I created it for those who want a unified experience without having to jump between separate courses.Practical Projects:SupervisedHouse Pricing (Regression)You'll apply regression models to predict property values based on location, size, age, and other features, using real data and deep exploratory analysis techniques.Customer Churn (Classification)You'll implement classification models to identify patterns that indicate a customer might leave a service, optimizing retention strategies with advanced metrics and predictive modeling.UnsupervisedCustomer SegmentationYou'll apply clustering models to group customers based on their behavior and features, optimizing business and marketing strategies through advanced multidimensional analysis.Product Recommendation SystemYou'll develop recommendation systems based on segmentation and consumption patterns, enhancing personalization using collaborative algorithms and hands-on implementation.This course is aimed at students and professionals who want to understand both ML approaches in a single course.It's for those who haven't taken my previous courses and want access to all the content in a concise, project-driven format.It also suits learners who prefer a practical and unified structure.This course is an honest and practical way to get valuable content in one seamless learning experience. See you inside the course!
Who this course is for
People interested in Machine Learning projects
Code:
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