Lifecycle of a Data Science Project → Defining the Problem Statement → Data Collection → Data Cleaning → Feature Engineering → Feature Selection → Data Preparation(Train, Validation & Test Split) → Model Building & Evaluation → Deployment → Model Monitoring & Retraining
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