Meticulous Data Scientist accomplished in compiling, transforming and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions to business problems.
Flexible and Adaptable
Statistics 101 - IBM
1. Cow Activity Prediction
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Objective : Classify Cow’s activities into 9 categories based on Data collected from IMU SENSORS
Methodology : Undertook all steps involved in data cleaning, preprocess, EDA and model building. Used Support Vector Machines , Logistic Regression, Decision Tree , Random Forest,K-Nearest Neighbors algorithms to build predictive model for this multi-class classification problem.
https://github.com/datapraveen/Batch-19-project-submission.git
2. Telecom Churn Prediction
Objective : Develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
Methodology : Undertook all steps involved in data cleaning, preprocess, EDA and model building. Used Support Vector Machines , Linear Regression, Decision Tree , Random Forest,K-Nearest Neighbors algorithms to build predictive model for this classification problem.
https://github.com/datapraveen/Batch-19-project-submission.git
Statistics 101 - IBM
Data Science 101 - IBM
Data Analysis with Python - IBM
Data Science Methodology - IBM
Data Science Tools - IBM
Data Visualization with Python - IBM
Machine Learning with Python - IBM
Predictive Modeling Fundamentals 1 - IBM
Skill Diploma in Digital Marketing – Digital Academy 360
Google Ads Certificates - Search, Display, Video, Shopping, App, Measurement
Microsoft Bing Ads Certification - Microsoft Advertising Certified Professional
SEMrush - Content Marketing and SEO Fundamentals, SEO Tool Kit
Linkedin Skill Assessment – SEO, Google Ads
Hub Spot – Content Marketing, Email Marketing