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Exploratory Data Analysis
Attributes
Determine the numeric and categorical attributes in the dataset
Statistical Descriptions
Basic Statistical Descriptions of Data - Mean, Median, Mode & Midrange
Dispersion of Data
Dispersion of Data: Range, Quartiles, Variance, Standard Deviation, and Interquartile Range
Missing Values
Handling missing values in the dataset
Handling missing values using Pandas & Numpy | Python Programming
Noise
Removing noise from the data using the Binning Technique | Pandas | Python Programming
Redundancy & Correlation Analysis
Redundancy & Correlation Analysis in Data Science | Python Programming
Data Reduction
What is Data Reduction? | Dimensionality Reduction | Numerosity Reduction | Data Compression
Duplicate Tuples
Remove duplicate tuples (rows) from the dataset | Python Programming
Outliers
What are Outliers & What is Outlier Detection?
Detecting and Filtering Outliers from Data
Outlier Detection using Supervised Learning Technique
Outlier Detection using Unsupervised Learning Technique
Skewed or Imbalanced Datasets
What are Skewed or Imbalanced Datasets?
Random Undersampling
Random Undersampling to Handle a Skewed Dataset
Principal Component Analysis
Principal Component Analysis | Scikit-Learn Implementation
Training and Testing
Creating training and testing sets from a single dataset