Data Pre-Processing and EDA
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Section 1: Introduction to Univariate Analysis
- Download Resources
- How to Get Queries Resolved
- Measures of Central Tendency
- When to Use Geometric and Harmonic Means
- Measures of Dispersion - Part 1
- Measures of Dispersion - Part 2
- Assignment
- Assignment Solution
Section 2: Significance Tests
- Chi Squared Test Theory and Maths
- Chi Square Test and Odds Ratio Demo
- ANOVA (Maths)
- ANOVA Concept (Intuition)
- ANOVA Demo
- Course Review
- Assignment
- Assignment Solution
Section 3: Data Imputation Methods
- Representing Missing Values
- Types of Missing Values
- Identifying Missing Values
- Visualize Missing Values with missingno
- When to Drop Rows and Columns
- Approaches to Filling in Missing Data
- Implementing Imputation
- Interpolation
- MICE Predictions - Part 1
- MICE Predictions - Part 2
- MICE Predictions - Part 3
- Validating Missing Value Imputations
- Course Review
- Assignment
- Assignment Solution
Section 4: Outlier Detection Approaches
- What are Outliers and Why They Matter
- Detecting Outliers with Box and Whiskers Plot
- Detecting Outliers with Z Score
- Ways to Treat Outliiers
- Mahalanobis Distance - Part 1
- Mahalanobis Distance - Part 2
- Cooks Distance
- Isolation Forest Algorithm - Part 1
- Isolation Forest Algorithm - Part 2
10.Isolation Forest Algorithm - Part 3
- LOF Part 1 Introduction
- LOF Part 2 Problem with simple density
- LOF Part 3 K Distance and Local Reachability Density
- LOF Part 4 Main Concept
- LOF Part 5 - Python Demo
- Local Outlier Factor Algorithm - Part 6
- Assignment
- Assignment Solution
Section 5: Feature Encoding Approaches
- Label Encoding
- Need for Feature Encoding
- Label and Ordinal
- One Hot Encoding
- Frequency Encoding
- Target Encoding - Part 1
- Target Encoding - Part 2
- Blending Method- Part 1
- Blending Method- Part 2
- Leave One Out Encoding
- Weights of Evidence and Information Value
- Weights of Evidence for Continuous Dependent
- Course Review
- Assignment
- Assignment Solution
- Need For scaling
- Standardardization and Normalization
- Robust Scaling
- Assignment
- Assignment Solution
Section 7: Plotting for Data Analysis
- Getting started with Matplotlib
- Making your first plot- Part 1
- Color, Marker and Style- Part 2
- Controlling plot components- Part 3
- Plotting two sets of points- Part 4
- Axis Ticks Positions- Part 5
- Anatomy of a Matplotlib Plot- Part 6
- Annotations- Part 7
- Analysing relationships between numeric variables
- Analyzing Distributions Histogram- Part 1
- Bar Charts
- Analysing Distributions Boxplots- Part 2
- Numeric vs Cat Overview- Part 1
- Numeric vs Cat Multi Box Plots- Part 2
- Numeric vs Cat Bubble Plots- Part 3
- Numeric vs Cat Pairs and Trellis- Part 4
- Categorical vs Categorical
- How is Analyzing Time Series different
- Line Plot
- Dual Axis Time Series Plot
- Interpreting ACF and PACF Plots.
- Assignment
- Assignment Solution
Section 8: Project and Assignment
- EDA Project - Classification Part - 1
- EDA Project - Classification Part - 2
- EDA Project - Classification Part - 3
- EDA Project - Classification Part - 4
- EDA Project - Classification Part - 5
- Assignment
- Assignment Solution