Welcome to Dev-tyta's Profile π
- π Profession: ML Engineer
- π― Long Term Goals: Machine Learning Research Engineer with an Embedded Systems Engineering Background
- π Current Focus: Large Language Models, Facial Recognition, and Visual Questioning.
- π― Collaborations: Always up for ML and Computer Vision Projects
- π Content Creation: Pen down technical articles for self-growth
- π Pronouns: He/Him
- β‘ Fun Fact: If I'm not coding, you'll find me in the dreamland!
- π Connect with me: @tee-tyta
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HumanCount: Advanced Crowd Monitoring with Wellness Detection
- Technologies: Faster-RCNN, YOLO, PyTorch, FastAPI, TensorFlow, OpenCV
- Enhancements: Developed a dual-purpose system integrating crowd density analysis with emotional and physical wellness detection, utilizing advanced computer vision and AI algorithms for real-time insights.
- Impact: Pioneered public safety and wellness monitoring solutions, offering critical data for urban planning, event safety, and mental health awareness campaigns.
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MaizeFolioID: Precision Agriculture for Maize Health
- Technologies: InceptionNet, VGGNet, Streamlit, HuggingFace Hub, TensorFlow, Docker
- Enhancements: Engineered a robust image recognition application tailored for detecting foliar diseases in maize, incorporating deep learning models for accuracy and Streamlit for user-friendly access.
- Impact: Revolutionized agricultural disease management, significantly reducing crop losses and increasing yield for small to large-scale farming operations.
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LoanMe: AI-Enhanced Loan Eligibility Assessment
- Technologies: LightGBM, Flask, Scikit-learn, Pandas, NumPy
- Enhancements: Created a predictive financing solution employing machine learning to evaluate loan eligibility, emphasizing ethical AI to promote financial inclusion and prevent bias.
- Impact: Transformed the lending process for financial institutions, offering a scalable tool that improved risk assessment and supported fair lending practices.
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Workers Register: Enhanced Workplace Security through Facial Authentication
- Technologies: FastAPI, AES Encryption, OpenCV, TensorFlow, Face Recognition API
- Enhancements: Implementing a comprehensive facial authentication system for secure workplace access, integrating cutting-edge encryption for data protection and utilizing AI for accurate, real-time identity verification.
- Impact: Elevated corporate security measures and operational efficiency, providing a seamless and secure method for employee verification and access management.
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BreedsMaster: Comprehensive Pet Recognition and Wellness App
- Technologies: Vision Transformer (ViT), Transformer-based models, TensorFlow, PyTorch, FastAPI, Docker
- Enhancements: Building an innovative app for pet breed identification and wellness insights, using state-of-the-art AI to offer detailed pet care information, behaviour analysis, and health symptom detection.
- Impact: Helps foster a deeper understanding and bond between pet owners and their pets, contributing to improved pet care and early detection of health issues.
- Analyzing Netflix's Dataset (2021)
- My '21 Journey in Data Science
- Roles & Responsibilities of an ML Engineer