t
talhaansari7

Muhammad Talha

@talhaansari7

Customer Satisfaction is my First Priority

Pakistan
Englisch, Urdu
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
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!... Mehr lesen

Kompetenzen

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talhaansari7
Muhammad Talha
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

Datentechnik
I will do python data analysis and machine learning tasks on notebook and colab
KI-Integrationen
I will build genai, agentic ai, llm, rag apps, and ml,dl,CV projects

Arbeitserfahrung

Machine Learning Engineer

NUST • Vollzeit

Jan 2025 - Present1 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 • Teilzeit

Jun 2024 - Dec 20251 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.