Shubhang Gupta's repositories
Hacktoberfest
Participate in Hacktoberfest. Learn and get started. Contribute to open source. Make sure your pull requests are legitimate. Enjoy and have fun.
Hacktoberfest-2020
Make this Hacktoberfest a learning period and contribute to Great Open Source Projects.
Hacktoberfest-2k20
Repository for Hacktoberfest 2020 Meetup at NITK Surathkal
hacktoberfest2020-1
Submit 4 pull requests to earn swags (Tshirts + badges)
Hacktoberfest2020-2
Participate in Hacktoberfest. Learn and get started. Contribute to open source. Make sure your pull requests are legitimate. Enjoy and have fun.
HacktoberFest2020-3
Make your first PR! ~ A beginner-friendly repository. Add your profile, a blog, or any program under any language (it can be anything from a hello-world program to a complex data structure algorithm) or update the existing one. Just make sure to add the file under the correct directory. Happy hacking!
HacktoberfestPR2020
Make your first Pull Request and earn a free tee from GitHub!
HandsOn-Data-Analysis-and-ML
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 on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. 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 use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC. Day:1 In this project, Students will make use of Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. You will write code to import the data and answer interesting questions about it by computing descriptive statistics. They will also write a script that takes in raw input to create an interactive experience in the terminal to present these statistics. Technologies that will be covered are Numpy, Pandas, Matplotlib, Seaborn, Jupyter notebook. We will be giving the students a deep dive into the Data Analytical process Day:2 We will be giving the students an insight into one of the major fields of Machine Learning ie. Time Series forcasting we will be taking them through the relevant theory and make them understand of the importance and different techniques that are available to deal with it. After that we will be working hands on the bike share data set implementing different algorithms and understanding them to the core We aim to provide students an insight into what exactly is the job of a data analyst and get them familiarise to how does the entire data analysis process work. The session will be hosted by Shaurya Sinha a data analyst at Jio and Parag Mittal Software engineer at Microsoft.
hello-world
My first repository