Safal joined the MS in Business Analytics program here at Cal State East Bay in Spring 2017 and is expected to graduate in May 2019. I am one of the two co-directors of the MS Business Analytics program and also taught her a course in Machine Learning in fall 2018. In the Machine Learning course, we covered topics ranging from data wrangling, feature engineering, to supervised and unsupervised learning algorithms. Safal chose the Telco Customer Churn project from Kaggle as her course project. This project asks for behavior prediction to retain customers and the development of a focused customer retention program. Throughout this project, Safal has demonstrated a solid grasp of the process of applying machine learning. Using Jupyter notebook with Python for the project, she showcased her mastery of data preprocessing and cleaning, exploratory data analysis, data visualization, feature expansion and selection, various machine learning models such as logistic regression, KNN, random forest, and model selection. She has achieved an admirable prediction accuracy. In addition to Machine Learning, Safal has also excelled in many other courses relevant to data science and data analytics, such as database management, statistical learning with R, big data technologies, and optimization. Safal would be an ideal candidate for a position in data analytics/business analytics.

Safal joined the MS in Business Analytics program here at Cal State East Bay in Spring 2017 and is expected to graduate in May 2019. I am one of the two co-directors of the MS Business Analytics program and also taught her a course in Machine Learning in fall 2018. In the Machine Learning course, we covered topics ranging from data wrangling, feature engineering, to supervised and unsupervised learning algorithms. Safal chose the Telco Customer Churn project from Kaggle as her course project. This project asks for behavior prediction to retain customers and the development of a focused customer retention program. Throughout this project, Safal has demonstrated a solid grasp of the process of applying machine learning. Using Jupyter notebook with Python for the project, she showcased her mastery of data preprocessing and cleaning, exploratory data analysis, data visualization, feature expansion and selection, various machine learning models such as logistic regression, KNN, random forest, and model selection. She has achieved an admirable prediction accuracy. In addition to Machine Learning, Safal has also excelled in many other courses relevant to data science and data analytics, such as database management, statistical learning with R, big data technologies, and optimization. Safal would be an ideal candidate for a position in data analytics/business analytics.

Safal joined the MS in Business Analytics program here at Cal State East Bay in Spring 2017 and is expected to graduate in May 2019. I am one of the two co-directors of the MS Business Analytics program and also taught her a course in Machine Learning in fall 2018. In the Machine Learning course, we covered topics ranging from data wrangling, feature engineering, to supervised and unsupervised learning algorithms. Safal chose the Telco Customer Churn project from Kaggle as her course project. This project asks for behavior prediction to retain customers and the development of a focused customer retention program. Throughout this project, Safal has demonstrated a solid grasp of the process of applying machine learning. Using Jupyter notebook with Python for the project, she showcased her mastery of data preprocessing and cleaning, exploratory data analysis, data visualization, feature expansion and selection, various machine learning models such as logistic regression, KNN, random forest, and model selection. She has achieved an admirable prediction accuracy. In addition to Machine Learning, Safal has also excelled in many other courses relevant to data science and data analytics, such as database management, statistical learning with R, big data technologies, and optimization. Safal would be an ideal candidate for a position in data analytics/business analytics.