This repository contains completed python notebooks for IBM’s “Data Analysis with Python” course
- Identify and handle missing values
- Identify missing values
- Deal with missing values
- Correct data format
- Data standardization
- Data Normalization (centering/scaling)
- Binning
- Indicator variable
- Import Data from Module
- Analyzing Individual Feature Patterns using Visualization
- Descriptive Statistical Analysis
- Basics of Grouping
- Correlation and Causation
- ANOVA
Exploratory Data Analysis notebook
- Linear Regression and Multiple Linear Regression
- Model Evaluation using Visualization
- Polynomial Regression and Pipelines
- Measures for In-Sample Evaluation
- Prediction and Decision Making
- Model Evaluation
- Over-fitting, Under-fitting and Model Selection
- Ridge Regression
- Grid Search
Model Evaluation and Refinement notebook
- House Sales in King County, USA