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4. Dealing with categorical features
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5. One-hot encoding and dummy variables
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6. Dealing with uncommon categories
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7. Numeric variables
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8. Binarizing columns
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9. Binning values
Learn Generative AI | Machine Learning | Deep learning | Artificial Intelligence - Material, Books, Videos, Exercises pinned «———————————————— —— —— #MODULE8 ———— ———————————————— 👇Inferential Statistics with Python👇»
Learn Generative AI | Machine Learning | Deep learning | Artificial Intelligence - Material, Books, Videos, Exercises pinned «———————————————— —— —— #MODULE9 ———— ———————————————— 👇Feature Engineering👇»
Learn Generative AI | Machine Learning | Deep learning | Artificial Intelligence - Material, Books, Videos, Exercises pinned «PART 1. Creating Features ———————— #MODULE9 #FeatureEngineering»
Learn Generative AI | Machine Learning | Deep learning | Artificial Intelligence - Material, Books, Videos, Exercises pinned «PART 2. Dealing with Messy Data ———————— #MODULE9 #FeatureEngineering»
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1. Why do missing values exist
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2. How sparse is my data
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3. Finding the missing values
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4. Dealing with missing values (I)
5. Listwise deletion.mp4
24 MB
5. List wise deletion
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6. Replacing missing values with constants
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7. Dealing with missing values (II)
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8. Filling continuous missing values
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9. Dealing with other data issues