Skip to content
View PartiGayatri's full-sized avatar
3 followers · 4 following
Block or Report

Block or report PartiGayatri

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
PartiGayatri/README.md

Hey there, I'm Gayatri 👋

Welcome to my GitHub profile! I'm passionate about Data Science, Machine Learning, and Software Development. Here, you'll find a collection of my projects, contributions, and repositories that reflect my journey and work in these fields.

About Me

  • 🎓 Education: Currently studying Computer Science (Data Science) in Vignan's Institute of Management and Technology for Women, Hyde

  • 🌱 Currently Learning: I'm currently diving deep into data science and exploring the fascinating world of machine learning.

  • 👀 Interests: I'm particularly interested in artificial intelligence, data visualization, and applying machine learning techniques to solve real-world problems.

  • 💞 Looking to Collaborate On: I'm eager to collaborate on exciting data science and machine learning projects.

  • 📫 How to reach me: Contact me on github

    I'm always open to discussing new projects, creative ideas, or opportunities to collaborate. If you're looking to collaborate on exciting data science or machine learning projects, feel free to reach out!

Popular repositories Loading

  1. PartiGayatri PartiGayatri Public

    1

  2. baseline-model-for-classification-of-openset-LID baseline-model-for-classification-of-openset-LID Public

    Jupyter Notebook 1

  3. heart-failure-prediction heart-failure-prediction Public

    Predicting heart failure using Decision Tree algorithm with a dataset sourced from Kaggle. Achieved 99% accuracy, demonstrating robust performance as a binary classifier.

    Jupyter Notebook