Detail-focused Data Analyst with knowledge in data warehousing, process validation and business needs analysis. Proven to understand customer requirements and translate into actionable project plans. Dedicated and hard-working with passion for Big Data.
Machine Learning
Data Mining
Analytical Thinking
Statistical Analysis
Normalization Techniques
Deep Learning
Critical Thinking
Data Visualization
Python Programming
Artificial intelligence
SQL
Advance Excel
Obstacle Avoiding Robot is an intelligent device that can automatically sense the obstacle in front of it and avoid them by turning itself in another direction.
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads. Some of the current systems learn driver patterns and can detect when a driver is becoming drowsy.
Developed an innovative Monument Information Generator (MIG) utilizing state-of-the-art deep learning models, including natural language processing (NLP) and computer vision. This project involved designing, implementing, and deploying a system capable of automatically generating descriptive information about historical monuments based on images. Key responsibilities included data collection and preprocessing, model training and optimization, and integration with web platforms to provide users with accurate and informative descriptions, enhancing cultural heritage accessibility and visitor engagement.