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Name: Niranjan Kumar Kishore Kumar

Type: User

Company: Yeshiva University

Bio: Master's graduate in AI with a keen interest in healthcare technology and data. Committed to solving real-world problems through innovative solutions.

Location: New York

Hi , I'm Niranjan Kumar

AI | Data Scientist |Biomedical Engineer

niranjan-kumar-k/ niranjan_kumar_nk_

This is ME, Niranjan Kumar, a Master Graduate from Yeshiva University (Katz School of Science and Health ), New York.
I'm unique blend of expertise in Artificial Intelligence (AI) and a Biomedical Engineer  ,
positions me as a valuable asset in the development of healthcare applications powered by AI. With my deep understanding of both the biological aspects of healthcare and the technical intricacies of AI algorithms, I'm well-equipped to tackle complex challenges and drive innovation in the industry improving myself and wants a platform to grow and excel  .
Progressing with PASSION and PERSISTENCE!!!!

Unicorn

 Talking about ME...

  • 😄 Pronouns: He/His
  • 🏆 UC Berkeley Generative AI Hackathon Winner.
  • 🌱 I’m currently learning LLM's , Gen AI
  • 🔭: I’m currently working on end to end ML projects.
  • 💬: Ask me about Machine Learning algorithms. 📊📈🤖🧠
  • 🤔 I’m currently open for a new job opportunity, this is [MY RESUME].
  • 💥 You can visit MY WEBSITE.
  • 📫 How to reach me [email protected]

🛠️ Skills

Languages

    R   C++   MATLAB   SQL

Framework and Libraries

Data Mining

Data Processing & Modeling

Data Visualization


Database & Cloud

    AWS

IDE Software & Tools

  Git   GitHub   Jupyter Notebook   Visual Studio Code

  Postman   Heroku   Django   Flask    

📄📜 Stats

🌟 Tʜᴏᴜɢʜᴛ ᴏғ ᴛʜᴇ Dᴀʏ 🌟

Niranjan Kumar Kishore Kumar 's Projects

aim5005 icon aim5005

Repo for the AIM 5005 course package

opencv-course icon opencv-course

Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.

project_1-convolutionnn-dog_dataset- icon project_1-convolutionnn-dog_dataset-

Developed a Custom Convolution Neural Network Architecture model for the Image Classification Problem and compared the accuracy with VGG16 pre-trained model.

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