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👋 Hey, I'm Subahani !

I'm a dedicated and passionate ML and Gen AI Engineer with expertise in models like GPT, Open-Source LLMs, and GANs. I specialize in NLP using NLTK, spaCy, and Transformers. My experience extends to developing ML models with TensorFlow and Scikit-Learn.

I have extensive experience in ASP.NET, building scalable web applications, and robust back-end services. Proficient in C#, I integrate complex business logic and design RESTful APIs for seamless communication. Skilled in MSBI tools, I handle ETL processes with SSIS and generate reports with SSRS. Additionally, I'm adept at SQL Server, including complex queries and database optimization. I enjoy creating innovative solutions and continuously expanding my skill set.

Feel free to explore my repositories and contributions. I'm always eager to collaborate on exciting Machine Learning and Generative AI projects and discuss innovative ideas!

🛠️ Skills

  • Programming Languages: Python, C#, Javascript
  • Machine Learning Frameworks: TensorFlow, PyTorch
  • Natural Language Processing: NLP techniques, libraries (e.g., NLTK, spaCy)
  • Web Development: ASP.NET, ASP.NET MVC Core, REST API
  • Business Intelligence: SSIS, SSRS
  • Data Visualization: Matplotlib, Seaborn, Plotly
  • Databases: SQL Server, Oracle
  • Vector Databases: ChromaDB, FAISS, Pinecone
  • Tools & Platforms: Visual Studio, Git, TFS

📫 You can also find me on

Syed Subahani's Projects

appliedaicourse icon appliedaicourse

This repo has all the code files which were created as part of the assignments to complete the Applied AI Course. The credit for code source structure and data goes to the Applied AI team.

imbalanced-data-with-smote-techniques icon imbalanced-data-with-smote-techniques

This repository contains implementation of some techniques like SMOTE, ADASYN, SMOTE + Tomek Links, SMOTE + ENN to overcome class imbalance in a binary classification problem.

stroke_prediction icon stroke_prediction

A predictive model for stroke diagnosis using logistic regression and upsampling(SMOTE)

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