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Data Pre-processing Steps:
1: Data Cleaning (Impute missing values, smoothing noisy data, Outliers, Inconsistancies)
2: Data Integration (Duplicates, Data Integrate, Data Merging, Data Consolidation)
3: Data Transformation (Scaling, Normalization, Aggregation, Generalization, Higher Level Concepts)
4: Data Reducdency (Dimensionality reduction, Numerosity Reduction--> Data Encoding, Data Compression)
5: Data Discretization (Converting Numerical --> Categorical , Binning, Clustering)
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Done
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Done
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I learned Data Pre-processing.
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I learned Data Pre-processing. These concepts are clear.
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Data pre-processing in more detail steps in this lecture. Must note down all points from the previous lecture as well as this lecture.
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AOA, I learned in this lecture about the key steps of pre-processing the data:1: Data Cleaning (missing values, smoothing noisy data, outliers, and inconsistency)
2: Data Integration (data integration, data duplicates, data merging, and data consolidation)
3-Data Transformation (scaling, normalisation, aggregation, generalization, higher-level concepts)
4: Data Reduction (dimensionality reduction, numerosity reduction, data compression)
5-Data Discretization ( a numeric variable converted into a categorical variable, binning, clusters).
ALLAH KAREEM ap ko dono jahan ki bhalaian ata kry AAMEEN.
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