rahulkinra Goto Github PK

100daysofmlcode

adiiton-hacktoberfest

basic-program-in-c-

big-data-hadoop-foundations

bugbounty-cheatsheet

A list of interesting payloads, tips and tricks for bug bounty hunters.

cpp

This repo contains all the C++ programs that are made as part of Object Oriented Programming subject.

datastructurespractice

ds

front-end-web-developer-1-nanodegree-udacity

FRONT END WEB DEVELOPER 1 NANODEGREE-UDACITY

hacktober-fest

hacktoberfest2020

Make your first PR. A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a simple program to a complex data structure algorithm). Happy coding...

html-css-js-project

ieee_ciet_sb_full_website

IEEE CIET SB Website

link-extractor-using-python

mini-web-search

Python Project

ml_assignments

ml_project

my-project

programming-hacktoberfest-2020-

Code -> Commit -> Earn

pyhton

python-acadview

Python Assignments

python-ml-chitkara-workshop

Workshop at Chitkara 19-20 July

python-programs

Full Stack Batch 2016-2020

python_notes

susi_server

Software and Skills for Personal Assistants using SUSI AI / Artificial Intelligence for Chat Bots https://api.susi.ai

testing3

us_bikeshare_data

Over the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles for short trips, typically 30 minutes or less. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will perform an exploratory analysis on data provided by Motivate, a bike-share system provider for many major cities in the United States. You will compare the system usage between three large cities: New York City, Chicago, and Washington, DC. You will also see if there are any differences within each system for those users that are registered, regular users and those users that are short-term, casual users.