Skip to content
View sumitdeole's full-sized avatar
5 followers · 5 following

Achievements

Achievement: QuickdrawAchievement: YOLOAchievement: Pull Shark
BetaSend feedback

Achievements

Achievement: QuickdrawAchievement: YOLOAchievement: Pull Shark
BetaSend feedback
Block or Report

Block or report sumitdeole

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
sumitdeole/README.md

Hello there!

Hi, I'm Sumit, a trained data scientist and experienced economist with over 4 years of experience. I thrive on diversity, innovation, and continuous learning. My interests span from Python/SQL programming to applying solutions in various domains, such as NLP and E-commerce.

  • 🧠 I'm currently exploring Machine Learning and Deep Learning.
  • ⚡ Currently upscaling with a Data Science Bootcamp at WBS coding school.
  • 🤝 Open to collaborations in Data Science and Data Product Management.

Skills

Python Rlang Git MySQL TensorFlow Google Cloud

Socials

GitHub LinkedIn

Badges

My GitHub Stats

Sumit's GitHub Stats

Pinned

  1. make-sales-happen make-sales-happen Public

    This project uses computer vision to implement an end-to-end solution for offline retailers to target their sales efforts toward more valuable customers in the store in real-time.

    Python

  2. data-pipelines data-pipelines Public

    Scooter-sharing system use case: This project demonstrates a local and cloud execution of automated data collection and cleaning pipelines.

    Jupyter Notebook 1

  3. llms-from-rag-to-chatbots llms-from-rag-to-chatbots Public

    LLM usecase: This project uses Langchain and Llama libraries to fool around with LLM models.

    Jupyter Notebook

  4. data-cleaning-project data-cleaning-project Public

    E-commerce use case: This project conducts a comprehensive data cleaning exercise on the eCommerce data.

    Jupyter Notebook 1

  5. daxeda/unsupervised_ml_moosic daxeda/unsupervised_ml_moosic Public

    In this project, we will apply different unsupervised machine learning clustering techniques on Spotify data to classify 5000 songs into 25 playlists.

    Jupyter Notebook 1

  6. supervised-ml supervised-ml Public

    This project uses the famous housing price prediction dataset and employs the two supervised ml algorithms (classification and regression).

    Jupyter Notebook 1