The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022
Each record represents one customer, and contains details about their demographics, location, tenure, subscription services, status for the quarter (joined, stayed, or churned), and more!
The Zip Code Population table contains complimentary information on the estimated populations for the California zip codes in the Customer Churn table
We need to predict whether the customer will churn, stay or join the company based on the parameters of the dataset.
| Machine Learning Models Applied | Accuracy |
|---|---|
| Random Forest | 78.11% |
| Logistic Regression | 78.28% |
| Naive Bayes Gaussian | 36.77% |
| Decision Tree | 77.29% |
| XGB_Classifier | 80.86% |
COVID-19 cases at daily level is present in covid_19_india.csv file
Statewise testing details in StatewiseTestingDetails.csv file
To analyze the COVID-19 data in India and determine the cure, death and active cases rates in all States. Plotting the active cases in states as on end date i.e. 8th May 2021
The ability to predict and analyze COVID-19 data will result in better understanding of the trends in Covid cases of India and will be of great help to government for taking precautionary measures
To control and manage the COVID-19 epidemic, and to effectively prevent and respond to future epidemics
This project follows the MIT LICENSE.
