4_​clustering k means_​empty

train

Model requirements

Data Collection

Data Cleaning

Data Labeling

Feature Engineering

Model Training

Model Evaluation

Model Deployment

Model Monitoring

Model requirements

Mall_Customers

Problem Identification

Objectives & Resources

Data Collection

Load Data

Raw Data Extraction (CSV Reader)

Understand Data (Statistics)

Data Cleaning

Filter Columns that are important (Column Filter)

Add missing values (Missing Value)

Data Labeling

Feature Engineering

Prepare Variables (Normalizer)

Model Training

k-Means

Model Evaluation

Scatter Plot

Model Deployment

Decistion Tree Learner