Supervised/Unsupervised Machine Learning Projects

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!

Overview

Section 1: Environment

Lecture 1 Introduction

Lecture 2 Environment Preparation 1

Lecture 3 Environment Preparation 2

Lecture 4 Environment Preparation 3

Section 2: Supervised Machine Learning

Lecture 5 Housing Appraisal 1

Lecture 6 Housing Appraisal 2

Lecture 7 Housing Appraisal 3

Lecture 8 Customer Churn 1

Lecture 9 Customer Churn 2

Lecture 10 Customer Churn 3

Lecture 11 Customer Churn 4

Lecture 12 Customer Churn 5

Lecture 13 Customer Churn 6

Lecture 14 Customer Churn 7

Section 3: Unsupervised Machine Learning

Lecture 15 Customer Segmentation 1

Lecture 16 Customer Segmentation 2

Lecture 17 Customer Segmentation 3

Lecture 18 Customer Segmentation 4

Lecture 19 Customer Segmentation 5

Lecture 20 Customer Segmentation 6

Lecture 21 Product Recommender 1

Lecture 22 Product Recommender 2

Lecture 23 Product Recommender 3

Lecture 24 Product Recommender 4

Lecture 25 Product Recommender 5

Lecture 26 Product Recommender 6

Lecture 27 Product Recommender 7

Lecture 28 Product Recommender 8

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