Sousse, Tunisia 4001 | +21693028964 | chaouch.thameurtc61@gmail.com
As an experienced textile engineer with a background in industrial processes, I am eager to apply machine learning to real-world problems. I have achieved a 10% reduction in knitwear costs and a 5% increase in washing/dyeing profits at Benetton. I improved subcontractor efficiency from 35% to 60% through cross-functional teamwork. Currently, I am seeking a career change into the field of artificial intelligence.
Below are some of my skills, and I'm always looking to learn more.
Experienced in both supervised and unsupervised learning, with a focus on object detection using YOLO. Proficient in clustering techniques, specifically K-means.
Specialized in computer vision with expertise in YOLO for object detection. Proficient in using frameworks and libraries such as TensorFlow, Keras, OpenCV, NumPy, Gensim, and Scikit-learn.
Proficient in Docker and Kubernetes for containerization and orchestration. Experienced in version control using Git and GitHub Actions.
Skilled in web development using Django, Flask, and FastAPI.
Proficient in Python and SQL.
Arabic (Native), French (B2), English (C1)
Here you can see some of the projects I've done on my own time.
In my free time, I continue to work on personal projects and have many ideas just waiting to be realized.
A brief summary of my professional journey.
Expected Graduation
Currently pursuing a dynamic Computer Science Engineer's degree at Holberton School Lac 1, specializing in Machine Learning, and set to graduate in July 2024. The curriculum places a strong emphasis on both supervised and unsupervised learning methodologies, providing a comprehensive understanding of advanced algorithms and artificial intelligence techniques. Engaged in project-based learning, addressing real-world challenges in the realm of Machine Learning. This approach not only cultivates practical skills in data analysis, feature engineering, and model evaluation but also fosters creativity and adaptability in problem-solving. Eager to apply this multifaceted education to contribute to innovative solutions in the field of Machine Learning upon graduation
Conducted daily calculations for industrial costs related to crushers. Resolved price reclamation cases by inspecting sewing lines, reformulating tailoring costs, and comparing with internal costs. Led efficiency projects to increase efficiency and enhance productivity.
Conducted daily checks on the progress of lean manufacturing projects. Worked on methodologies such as VSM, SEMD, and 5S.
Proud graduate of the National Engineering School of Monastir, Monastir, with a specialization in Textile Engineering, conferred in July 2018. The program provided in-depth knowledge of textile manufacturing processes, materials, and technologies. Hands-on experience in textile laboratories and industry-relevant projects honed my skills in quality control, process optimization, and innovation within the textile sector. Collaborative projects and coursework have not only enriched my technical expertise but also cultivated effective communication and teamwork skills crucial for success in the textile engineering domain. Ready to contribute my skills and knowledge to drive innovation and excellence in the textile industry
At IPEIM, I built a solid base in math, science, and computer science, exploring various engineering disciplines through electives. My studies covered calculus, physics, chemistry, programming, and technical English, preparing me for future university engineering challenges and immersing me in a supportive learning environment.
Below are my Certifcations.
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network
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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
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you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case. You will also implement workflow automation and progressive delivery that complies
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In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
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Delve deeper into the processes and concepts behind APIs and their infrastructure. Explore the key concepts that underpin API development and the principles of representational state transfer architectural style (REST) architecture. Build basic API and REST data backbones for web apps using Django. Discover emerging API technology and practice other ways to build and work with APIs.
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