salman shaikh
About Candidate
data science and machine learning enthusiast . looking forward for the opportunites for industrial experience
Skills
Location
Education
Work & Experience
Performed EDA before feeding data to the machine. Sampling done as data was unbalanced also used scaling on Training and testing data. Trained and tested the dataset using different algorithms of classification to achieve good predictive models. Logistic Regression got better prediction results.
Performed EDA to check null and missing values in the dataset also checked correlation. Linear Regression for Training and than testing. Assumptions of Linear Regresssion considered such that we may get more accurate prediction. Polynomial Regression to improvise the score of prediction as linear assumptions was not fulfilled usage of polynomial regression was must.
To reduce customer churn,telecom companies need to predict which customers are at high risk of churn. Build predictive models to identify customers at high risk of churn and Identify the main indicators of churn.
Taking about the system it contains basic function which Include add students, view students, search students and remove the student. Flask Framework used.
