Anjali Sanjay Shinde anjalishinde1906

Anjali Shinde

Coming soon

Uncovered credit card transaction patterns within a dataset using advanced analytics.
Performed data wrangling and EDA on real-world data of 84,000+
Created quantile regression model with columns data and applied Recursive Feature Elimination to get top 10 features
Employed prescriptive analytics to analyze,outlier detection and provide actionable insights based on the identified patterns.
Explored and visualized the data, testing multiple algorithms to enhance fraud detection accuracy.
Concluded the analysis by implementing a Random Forest machine learning model, achieving an impressive 98% accuracy in fraud detection.

Curated a dataset of 29,000 leaf samples, ensuring data quality through cleaning and preprocessing.
Conducted statistical analysis and data exploration for insights.
Implemented machine learning algorithms, including Deep CNN, for accurate leaf identification.
Integrated Python ML services seamlessly with a React-based agricultural platform.
Deployed the functional platform for user testing and feedback.
Maintained and updated the system to address issues and incorporate improvements

Planned the structure of the application to efficiently handle attendance tracking, credit management, and notice dissemination.
Leveraged Python Flask to handle server-side logic, ensuring efficient processing of attendance, credits, and notices.
Utilized SQL through XAMPP to establish a robust relational database, enabling secure and organized storage of student and teacher data.
Implemented a user-friendly interface using HTML, CSS, and JavaScript to provide an intuitive experience for both students and teachers.
Addressed 70% of teachers' administrative tasks by automating processes related to attendance, credit management, and notice distribution.
Facilitated the management of over 5000 students through the CRUD application, enhancing the overall efficiency of administrative tasks for both students and teachers.

Identified the need for an inventory management system to streamline inventory tracking and management processes.
Chose React for the frontend to ensure a responsive and dynamic user interface.Utilized MongoDB as the backend database for efficient data storage.
Employed JavaScript for both frontend and backend development.Implemented Node.js for server-side scripting to handle data processing.
Designed a user-friendly interface using React, providing a seamless experience for users.
Developed backend functionalities in Node.js, incorporating MongoDB for scalable and flexible data storage.
Conducted thorough testing to ensure the reliability and functionality of the web application.Addressed and resolved any issues through systematic debugging processes.
Deployed the inventory management system, making it accessible to users.

Graduate Teaching Assistant for Programming in Java | San Diego State University

👨‍💻 Software Developer | Tata Consultancy Services Pvt LTD

💻 Assistant Software engineer | Tata Consultancy Services PVT LTD


Anjali Shinde