Problem Solving Architecture
Data Gathering
Frame The Problem
Data Loading
Data Integration
Know The Current Solution
Know the Final Objective
Understanding the Business Problem
Data Fetching
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Explore Data To Gain Insights
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Finding Patterns and Trends
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Making raw data into meaningful
Feature Correlation
Prepare the Data to to Feed ML Algorithms
Feature Selection and Extraction
Feature Engineering
Data Scaling and Data Balancing
Imputation and Label Encoding
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Explore Different Models
Try Different Models
Short List Best Models
Know the Underlying Flow of Models
Fine Tune Your Models
Cross Validation
Parameter Tuning
Model Tuning
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