Skip to content
View vinamrata-git's full-sized avatar
💭
I may be slow to respond.
💭
I may be slow to respond.
Block or Report

Block or report vinamrata-git

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
vinamrata-git/README.md

Hi! hi Welcome to my github profile.

   



Open for hiring

Passionate and enthusiastic data scientist who enjoys working on target-based research and result-oriented problem solving.

About me

Timezone: Europe/France

I have 2 years of working experience as a data scientist

I hold a master's degree in data science (Polytech Nantes) and bachelor's degree in computer science. And I have done a data analytics bootcamp (Ironhack France) to strenghten my skill in data analytics.

Area of Interest:

  • Data analytics
  • NLP
  • Machine learning


Languages and Tools

Python Git Git Git VSCode Git Git


GitHub Commits Graph

Pinned

  1. Amazon-scraper-selenium-python Amazon-scraper-selenium-python Public

    Created an scraper using selenium and python to collect the data from multiple pages on amazon website

    Jupyter Notebook 5 5

  2. crimes-in-chicago crimes-in-chicago Public

    Forked from leo-cavalcante/crimes-in-chicago

    Regression and Statistical analysis of crimes in Chicago from 2015 until 2020.

    Jupyter Notebook 1

  3. Customer-analysis-using-Tableau Customer-analysis-using-Tableau Public

    This repository contains a dashboard created using Tableau and you will find details about customer analysis method

  4. Customer-Segmentation Customer-Segmentation Public

    KYC: know your customer. In this repository you will know the phases of B2C customer analysis and customer segmentation using k-means and RFM analysis