t
talhaansari7

Muhammad Talha

@talhaansari7

Customer Satisfaction is my First Priority

Paquistão
Inglês, Urdu
Algumas informações são exibidas no idioma inglês.
Sobre mim
I’m an AI Engineer and currently pursuing an MS in Artificial Intelligence and Autonomous Systems. I specialize in developing intelligent systems using machine learning, computer vision, and AI agent-based models. I’ve worked on real-world projects involving object detection, image classification, facial recognition, and automation. My skill set includes Python, OpenCV, PyTorch, TensorFlow, NumPy, Scikit-learn, Keras, Power BI, and Tableau. I’m committed to delivering scalable and innovative AI solutions tailored to your needs. Thank You!... Saiba mais

Habilidades

t
talhaansari7
Muhammad Talha
offline • 
Tempo médio de resposta: 1 hora

Conheça meus serviços

Engenharia de Dados
I will do python data analysis and machine learning tasks on notebook and colab
A partir deUS$ 45 /projetoMais detalhes
Integrações de IA
I will build genai, agentic ai, llm, rag apps, and ml,dl,CV projects
A partir deUS$ 120 /projetoMais detalhes

Experiência profissional

Machine Learning Engineer

NUST • Período integral

Jan 2025 - Present • 1 yr 4 mos

I am responsible for designing, developing, and deploying intelligent systems that can learn from data and make predictions or decisions without being explicitly programmed. Also focus on improving model accuracy, handling large datasets, and ensuring models can scale efficiently in production environments. Use programming languages like Python and tools such as TensorFlow, PyTorch, and scikit-learn. Further, collaborate with data analysts, software engineers, and business teams to translate data insights into practical applications.

Computer Vision Engineer

SubSeaScanning • Meio período

Jun 2024 - Dec 2025 • 1 yr 6 mos

Conducted comparative analysis of point cloud registration (KISS-ICP, 3DTK, Open3D); 3DTK offered best efficiency for large-scale mapping, while KISS-ICP was 2× faster (handling 6.5° rotation & 10% overlap), validated with CloudCompare. Developing an underwater marker detection system by fine-tuning Detectron2; achieved 90% detection accuracy, extracted marker centers across RGB & grayscale channels (except red), supporting bundle adjustment optimization.