M Shalbiya Mellat
fresher
Profile summary
Recent Master's graduate in Data Science and Business Analytics with expertise in Python, SQL, R, and machine learning. Demonstrated technical proficiency through impactful projects in gesture recognition and automated recruitment systems. Eager to apply analytical skills and data visualization expertise to drive business intelligence solutions.
Career highlights
Achieved 90% Gesture Recognition: Built a real-time gesture recognition model, achieving 90% accuracy using CNN, to support accessibility through real-time gesture-to-text translation.
Automated Recruitment Process: Developed a web-based virtual HR assistant using Python and NLP that reduced manual screening time by 60% in simulation tests.
Key skills
Professional experience
Project: Customer Segmentation Using k-Means Clustering Applied K-Means clustering on customer data to identify behavior based segments for targeted marketing, optimized clusters using Elbow method and visualized results for business insight using python and jupyter notebook
- Applied K-Means clustering on customer data to identify behavior based segments for targeted marketing
- Optimized clusters using Elbow method
- Visualized results for business insight using python and jupyter notebook
Education
Modules included: Machine Learning, Predictive Analysis, Natural Language Processing, Big Data Tools and Techniques, Applied Statistics, Deep learning, Advanced DBMS, JAVA and Data Structures, Data Mining, Regression Analysis, Management Information System, Business Environment, Ethical Hacking, Cloud Computing.
Modules covered: Data Structures, Computer Architectures,RDBMS, Data Communication and Computer Network, PHP and MySQL, Mobile Application Development, Software Engineering and Testing, Computer Graphics and Visualization, Internet of Things.