Data Analysis Demo (Categorical Variables) | Deployment of Machine Learning Models
In this final video of our Exploratory Data Analysis (EDA) series, we dive deep into categorical variables on how to understand their cardinality, map ordered categories, and identify rare labels that can affect model performance.
You’ll learn how to:
✅ Map qualitative labels (like Excellent → 5, Poor → 1) into meaningful numbers
✅ Detect and handle rare categories that may cause overfitting
✅ Visualize how categorical features influence the Sale Price
This lesson wraps up the EDA stage of our End-to-End Machine Learning Pipeline, setting the foundation for the Feature Engineering phase next!
🎓 Ready to build smarter models with cleaner data?
👉 Enroll in the course to follow every step from data exploration to deployment. https://www.trainindata.com/courses.
🔗 Link to presentations: https://www.trainindata.com/l/digital...
#MachineLearning #DataScience #FeatureEngineering #ExploratoryDataAnalysis #CategoricalData #DataPreprocessing #MLPipeline #PythonMachineLearning #Pandas #Kaggle #DataCleaning #TrainInData #LearnMachineLearning #DataAnalytics #MLCourse #AICourse #machinelearningcourse #machinelearningtutorial