As an MLOps developer, simulation specialist, and research engineer with over 6 years of experience, I specialize in developing innovative data-driven solutions. My tenure as a postdoc at NC Inc. was marked by leveraging machine learning and synthetic data from finite element simulations for thermal stress analysis in pipe bends, directly addressing industry challenges. In my current role at Arcurve Inc., I utilize cloud services (e.g., Azure and AWS) to develop/maintain end-to-end machine-learning pipelines. Additionally, my personal project 'DocsGPT,' a RAG-based querying app using LangChain and OpenAI's API, demonstrates my proficiency in implementing solutions using generative AI. Let's connect on LinkedIn.
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Arcurve Inc.
- Calgary
- https://www.linkedin.com/in/farhad-davaripour/
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Stanford-CS229-Spring2023-Notes
Stanford-CS229-Spring2023-Notes PublicCS229 course notes from Stanford University on machine learning, covering lectures, and fundamental concepts and algorithms. A comprehensive resource for students and anyone interested in machine l…
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CFRP_Reinforced_HDD_overbend
CFRP_Reinforced_HDD_overbend PublicThis project employs machine learning and synthetic dataset to predict the peak equivalent stress imposed on a CFRP wrapped HDD overbend
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Navigating_GenAI
Navigating_GenAI PublicThis repo includes the demos presented as a part of the "Navigating-GenAI" module within the DATA 691 capstone integrated topics course for the Master of Data Science and Analytics (MDSA) program a…
Jupyter Notebook
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Linear_regression_Core_Principles
Linear_regression_Core_Principles PublicBuilding a Linear Regression Model from scratch.
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