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Hi there šŸ‘‹

I'm Chhavi Sharma

A Data Scientist, passionate about harnessing the power of AI and Machine Learning to unravel complex problems

  • šŸ”­ Iā€™m currently working on LLM Generated Text Detection

  • šŸ‘Æ Iā€™m looking to collaborate on LLM Based Projects

  • šŸ“« How to reach me [email protected]

  • āš” Fun fact Good at Reading Books and Minds.Always up for any adventure.

Connect with me:

chhavi6vsharma cshar75

Languages and Tools:

aws azure blender c cplusplus csharp flask gcp git graphql hadoop hive javascript linux mariadb matlab mongodb mssql mysql nodejs opencv oracle pandas postgresql python pytorch scikit_learn seaborn sqlite tensorflow unity

chhavi's Projects

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

šŸ§‘ā€šŸ« 60 Implementations/tutorials of deep learning papers with side-by-side notes šŸ“; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), šŸŽ® reinforcement learning (ppo, dqn), capsnet, distillation, ... šŸ§ 

applied-ml icon applied-ml

šŸ“š Papers & tech blogs by companies sharing their work on data science & machine learning in production.

asl_to_english icon asl_to_english

Reads your hand signs and translates them to English words using Tensorflow object detection API

cookbook icon cookbook

A collection of guides and examples for the Gemini API.

courses icon courses

This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

data-science-cheatsheet icon data-science-cheatsheet

A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between.

distilabel icon distilabel

āš—ļø AI Feedback framework for scalable LLM alignment

made-with-ml icon made-with-ml

Learn how to design, develop, deploy and iterate on production-grade ML applications.

masked-diffusion-lm icon masked-diffusion-lm

Official implementation for the paper "A Cheaper and Better Diffusion Language Model with Soft-Masked Noise"

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