This is the Repository for understanding the work on Exploratory Data Analysis, Statistics & Machine Learning Models. In this repo you will find all the accompanying Jupyter (a.k.a. iPython) Notebooks.
-
Linear Regression Model & Assumptions Click Here
-
Big Mart Sales Project - EDA & Outlier Treatment Click Here
-
Predicting Sales - EDA, Feature Engineering & Machine Learning Model Click Here
-
Hypothesis Testing (One Sample & Two Sample T-Test) Click Here
-
Understanding Anova & Chi Square Test Click Here
-
One Way & Two Way Anova Examples Click Here
-
Black Friday Purchase Price Prediction - ML Models Click Here
-
Regularization Models (Ridge, Lasso & Elastic Net) Click Here
-
Healthcare Analytics - EDA, Feature Engineering & Machine Learning Model Click Here
-
Insurance Claim Prediction Problem - EDA, Feature Engineering & Machine Learning Model Click Here
-
Taxi Fare Prediction - EDA, Feature Engineering, Supervised & Unsupervised Machine Learning Click Here
-
Car Insurance Claim Prediction - EDA, Feature Engineering & Machine Learning Click Here
-
Principal Component Analysis on Wine Dataset - Understanding Clustering & PCA Click Here
-
Workathon Price Prediction Challenge - Text Cleaning & Feature Engineering Click Here
-
Food Demand Forecasting Click Here
- Understanding Data Science Using IPL Dataset Click Here
- Exploratory Data Analysis on Netflix Click Here
