The above project is python project

1. MAHARAJA INSTITUTE OF TECHNOLOGY
THANDAVAPURA
DATA S CIE NCE USING
PYTHON
Project : “Telecom churn Assignment”
TEAM (NAME & USN)
1. VIJAY KUMAR K M (4MN20EC034)
2. MANJUNATH N R (4MN20EC014)
3. PRANAV D K (4MN20EC018)
4. NIROOPARADHYA S R (4MN20EC016)

2. PROBLEM STATEMENT
Dept of ECE, Maharaja Institute of Technology Thandavapura
We have telecom data of many customers and the task is to predict whether the
customer will churn or not. 'Churn' means the customer will unsubscribe from the
plan and stop doing business with the company. A Telecom company wants to
predict this in advance and do something to address the issue or do something to
retain their customers.

3. INTRODUCTION
For Telco companies it is key to attract new customers and at the same time avoid contract
terminations (=churn) to grow their revenue generating base. Looking at churn, different reasons
trigger customers to terminate their contracts, for example better price offers, more interesting
packages, bad service experiences or change of customers’ personal situations.
Churn analytics provides valuable capabilities to predict customer churn and also define the
underlying reasons that drive it. The churn metric is mostly shown as the percentage of customers
that cancel a product or service within a given period (mostly months). If a Telco company had 10
Mio. customers on the 1st of January and received 500K contract terminations until the 31st of
January the monthly churn for January would be 5%.
Telcos apply machine learning models to predict churn on an individual customer basis and take
counter measures such as discounts, special offers or other gratifications to keep their customers.
A customer churn analysis is a typical classification problem within the domain of supervised
learning.
Dept of ECE, Maharaja Institute of Technology Thandavapura

4. Dept of ECE, Maharaja Institute of Technology Thandavapura
What is customer churn?
Customer churn is also called customer attrition. It is when customers stops using your
products or services. To be simple, it is when customers stops being your customer.

5. Dept of ECE, Maharaja Institute of Technology Thandavapura
How can machine learning help retaining
customers?
1. Machine learning could study the data and train model based on customer churn history.
2. Machine learning could predict customers with high probability to churn.
3. Company can develop special program for those who has the probability to churn

6. PROCEDURE
Dept of ECE, Maharaja Institute of Technology Thandavapura
Step 1: Problem Definition
Step 2: Data Collection
Step 3: Exploratory Data Analysis (EDA)
Step 4: Feature Engineering
Step 5: Train/Test Split
Step 6: Model Evaluation Metrics Definition
Step 7: Model Selection, Training, Prediction and Assessment
Step 8: Hyperparameter Tuning/Model Improvement

7. CONCLUSION
Dept of ECE, Maharaja Institute of Technology Thandavapura
 The importance of this type of research in the telecom market is to help companies make more profit.
 It has become known that predicting churn is one of the most important sources of income to Telecom
companies.
 Hence, this research aimed to build a system that predicts the churn of customers in telecom company.
 These prediction models need to achieve high AUC values. To test and train the model, the sample data is
divided into 70% for training and 30% for testing.

8. KNN ALGORITHM
Dept of ECE, Maharaja Institute of Technology Thandavapura
KNN ALGORITHM (OPTIMIZED)

9. LOGISTIC REGRESSION
Dept of ECE, Maharaja Institute of Technology Thandavapura
LOGISTIC REGRESSION(OPTIMIZED)

10. RANDOM FOREST
Dept of ECE, Maharaja Institute of Technology Thandavapura
RANDOM FOREST(OPTIMIZED)

11. Department of Electronics &
Communication Engineering
MITT
Dept of ECE, Maharaja Institute of Technology Thandavapura
THANK YOU !