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Using machine learning to predict customer churn in a telecom company
Identify patterns in customer behavior data
Build a predictive model to forecast which customers are likely to churn
Implement strategies to retain at-risk customers
Measure the effectiveness of the model in reducing churn rate
I have worked on projects involving natural language processing, computer vision, and recommendation systems.
Developed a sentiment analysis model using NLP techniques to analyze customer reviews
Implemented a facial recognition system using CNN for security purposes
Built a movie recommendation system based on collaborative filtering algorithm
Python code to find prime numbers in a given range
Iterate through the range of numbers
Check if each number is divisible by any number other than 1 and itself
If not divisible, then it is a prime number
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I appeared for an interview before May 2016.
based on 1 interview
Interview experience
Marpu Foundation
Huawei Technologies
HCL Infosystems
Z X Learning