End-to-End Project: Data Cleaning and Analysis [Under Construction] | CommonLounge

NaN.

End-to-End Project: Data Cleaning and Analysis [Under Construction][ Edit ]

From Data Cleaning and Analysis course

Choose your learning format:

Article

Cards

Note: This project is currently under construction. The final version is expected to be ready on or before June 15th 2019.

In this project, we will put together all the pieces we have learnt so far for data exploration, data cleaning and data analysis. This will include loading datasets, exploring numerical and categorical variables, data visualization, handling missing values, checking for outliers, performing data transformations, etc.

Let's get started!

Next →

Category: Machine Learning

Mark completed

Handling Duplicates, Missing values and Outliers [Under Construction]

About the contributors

SR

Srijith RajeevAI Enthusiast

KD

Keshav DhandhaniaMachine Learning @ MIT (2014). DM me for 1-on-1 mentorship (paid).

Part of course:

The student dataset
Type of Variables
Duplicate Observations
Distribution of Variables
Categorical Variables
Numerical Variables
Why bimodal / trimodal distributions?
Bimodal Distributions (Matriculation, Physics, Chemistry, Maths)
Trimodal distribution (Entrance Rank)
Numerical Variable Transformations
Log transformation
Percentage Transformation
Data Re-scaling: Standardization
Missing Values
Checking for missing values
Dealing with missing values
TODO: Imputing missing values
Imputation by Median / Mode of Subgroup
kNN Imputation
Recommended treatment for missing values
Final check
Outliers
Deleting Observations
Imputing
Segment and Analyze Separately
Transforming and binning values
No processing
Recommended method for Outliers
Categorical Variable Transformation
One hot encoding
KNN Imputation of Missing Values
Summary

Show admin stats