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Hi, I'm Arshpreet Singh Khangura, a Full Stack Developer šŸš€ from India, currently, I'm working at šŸ‘ØšŸ½ā€šŸ’¼[ITC].

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Talking about Personal Stuffs:

  • šŸ‘ØšŸ½ā€šŸ’» Iā€™m currently working on something cool šŸ˜‰;
  • šŸŒ± Iā€™m currently learning Quantum Computers and It's applications in Finance;
  • šŸ’¬ Feel free to reach me anytime;
  • šŸ“« How to reach me: Just drop an Email at [email protected];
  • šŸ“Resume

Languages and Tools:

šŸ“ˆ My GitHub Stats

arshpreetsingh

Arshpreet Singh's Projects

advent-2017 icon advent-2017

Write a Kubernetes-ready service from scratch step-by-step

alipay-scrapper icon alipay-scrapper

A webapp using requests module to fetch data from Alipay and saving MySql DB

awesome-quant icon awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

batterysaver icon batterysaver

This is python battery saver pack still in very rough development stage

bitcoin icon bitcoin

Bitcoin Core integration/staging tree

celery-asynchronous-web icon celery-asynchronous-web

Django celery is used for Asynchronous web, Developer can add multiple workers/tasks can execute simultanioulsy without making any delay for user to wait for any task.

certifications icon certifications

Repository for All online learning certificates those I have completed

chatapp icon chatapp

Asynchronous Chat Application Written Golang!!

dataanalytics icon dataanalytics

Jupyter notebooks explaining usage of Python for Finace using DataScience and Machine learning

deeplearning.ai-summary icon deeplearning.ai-summary

This repository contains my personal notes and summaries on [DeepLearning.ai](deeplearning.ai) course. I've enjoyed every little bit of the course hope you enjoy my notes too.

deeplob-deep-convolutional-neural-networks-for-limit-order-books icon deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

divine-learning icon divine-learning

All the methods and tutorials based on the learning based on many new methods.

dpr icon dpr

Digital Profile Reporting

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