Nidhi O.

Nidhi O.

Python Developer with 2 YOE having strong foundation over data structure and algoritham

New Delhi , India

Experience: 2 Years

Nidhi

New Delhi , India

Python Developer with 2 YOE having strong foundation over data structure and algoritham

17349.3 USD / Year

  • Immediate: Available

2 Years

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About Me

I'm a Mtech passout(2020) from NIT Patna, currently working as a software developer in GSDL, Delhi, having 2+ YOE. I have a solid foundation in Python, Flask, Data-Structure & Algorithm, C, with core CS subjects expertise. 

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Portfolio Projects

Online job portal

https://gsdl.org.in:5000

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Project L

Company

Online job portal

Description

Working on tech-stack on Python Flask MongoDB-based project.

Build a secure system for users to create their profile and see current openings and apply to the job.

Implemented secure login and authorization module using OTP verification.

File read and write a module for document verification by user-admin.

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Online Cart Management System

https://github.com/nidhiojha/eCommerce_CLI

Company

Online Cart Management System

Role

Backend Developer

Description

This CLI Application contains CRUD items with Cart addition and deletion capability. ● Each operation except the Search item requires user/admin credentials. In C-U-D methods authorized users only can do the operations. ● User/Admin can Register themself. For cart operations only Admin can add new products to the list and users can add those products to their cart. ● Admin has permission to add coupons per product as well as can modify the accessibility of the coupons per product. ● User can buy/add multiple products from the cart as well as can view the coupons available at any point of time and can apply to it but it can access only one time and can get a discount based on the final billing stage. ● For remove (DELETE) items, only Admin who added the item previously is allowed to delete, Bill generated after checkout from the cart including discounts and after applying coupon.

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: A Comparison Based Breast Cancer High Microscopy Image Classification Using Pre-trained Models

Company

: A Comparison Based Breast Cancer High Microscopy Image Classification Using Pre-trained Models

Description

In this paper, I have used various deep CNN architectures to classify high microscopic breast cancer tissue images and compare their performance based on accuracy, precision, recalls, and F1-scores. ● Even if there are a limited number of data sets I perform some techniques to overcome this problem and trained my model which uses some techniques to avoid over-fitting. ● For classification purposes we have used the LightGBM method. ● Also our model gives the best result with the minimum error rate compared to all other previously worked done. ● In this paper I had used strong preprocessing techniques on images to extract features more precisely and did various experiments to achieve the desired result, and the result I achieve gives promising results.

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Skills

Python