chiragbiradar Goto Github PK

followers: 52.0 following: 28.0 repos: 64.0 gists: 0.0

Name: Chirag Biradar

Type: User

Company: KLE Technological University

Bio: learn, grow, leave a mark.

Location: India

Blog: https://chiragbiradar.me/

💫 About Me:

Hello there! My name is Chirag Biradar. I'm passionate about DevOps and cloud computing, with a keen interest in the ever-exciting field of cybersecurity. I love tinkering with code and enjoy exploring new technologies, always seeking to expand my skill set. Whether it's development or deployment, I'm up for the challenge. As an enthusiastic learner and dedicated team player, I'm excited to collaborate and contribute to innovative projects on GitHub. So let's connect and create something amazing together!

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Chirag Biradar's Projects

100-days-of-python

A journey through 100 days of python course by Dr. Angela Yu, documented and shared on Github.

action-repo

algoexpert

Solutions to problems that I solved on AlgoExpert.

algoexpert-170-coding-interview-questions

This is a Github repository where I will be sharing my journey of preparing for AlgoExpert's 170 Coding Interview Questions. I will be categorizing the questions by difficulty level and exploring different approaches for each problem with varying space and time complexities.

asmapy

Asmap stuff for Bitcoin Core

bitcoin

Bitcoin Core integration/staging tree

chai-backend

A backend project from ChaiAurCode YouTube channel By Histesh Choudhary

chatty

chiragbiradar

cloud-native-monitoring-app

computer_networks

content-engine

covid-19-vaccination-analysis

The repo contains COVID -19 VACCINATIONS ANALYSIS and time series predection technique to predict completion of vaccination process.

cp-templates

Here are my template codes for Competitive Programming with optimised implementations of various algorithms. I personally use them every day and have tested almost all of them in multiple competitive programming contests and practice problems

crackyourplacement

ddos-attack-detection-and-mitigation

SDN networks (Software Defined Networking ) are exposed to new security threats and attacks, especially Distributed Denial of Service (DDoS) attacks. For this aim, we have proposed a model able to detect and mitigate attacks automatically in SDN networks using Machine Learning (ML)