Machine learning projects

Developed a deep learning model to conduct multiclass image classification of six categories: buildings, forests, mountains, seas, streets, and glaciers. Utilized Convolutional Neural Networks (CNNs) and transfer learning, ex: the Inception ResNet V2 model.

Developing a robust eligibility evaluation model for customers on the cusp of loan approval with the goal of decreasing default. Utilizing Python and SQL in risk analytics. 

Analyzed 200k news articles to identify industries and jobs vulnerable to AI impact. Delivered actionable insights and recommendations for task automation, productivity enhancement, and AI-hesitant industries using NLP and LLMs in GCP.