AJAY SHINDE

Motivated student eager to apply classroom knowledge to real-world experiences, with a strong willingness to learn and contribute. Effective communicator with a collaborative mindset, ready to bring fresh perspectives and a strong work ethic to any team.

• Successfully built projects showcased in academic exhibitions.
• Recognized for excellence in app development in university-level competitions.
• Class Representative for one semester at MIT-WPU.

Farmer Care App

Developed a mobile application that provides farmers with real-time weather updates, crop management tips, and market prices Served over 1,000 farmers, enabling them to make informed decisions and improve productivity.

DragGAN

Generative Adversarial Network for Image Processing: Implemented a GAN model, enabling intuitive image editing and manipulation. Users can alter image features, like shapes and textures, interactively, showcasing advanced applications of deep learning.

Urban Infrastructure Impact Prediction

Utilized Conditional GANs (cGANs) and CycleGANs for predicting urban infrastructure impacts. Implemented using Python with TensorFlow and PyTorch frameworks.

E-Commerce Sales Analysis

Personal Project: Analyzed over 500,000 rows of e-commerce sales data using SQL and Python to identify revenue trends and customer behavior, and developed a predictive model to forecast sales, achieving 85% accuracy.

Created Tableau dashboards for visualizing revenue, customer segments, and product performance.

• Data Analysis
• Artificial Intelligence
• Machine Learning
• Deep Learning