This repository contrains all the resources from the fifth sesison of the NYU Data Science Bootcamp. In this session, we covered the basics of Machine Learning - Regression and Clustering.
Instructor: Sagar Patel
The recording of the session can be found here
Submission due: July 15th, 2021
In the final project, you will apply the tools you have learned in this BootCamp to solve a realistic problem.
Due to shortage in number of sessions and the fact that this BootCamp is beginner centric, it is NOT mandatory to present the project to obtain the certificate. The presentation and demo will be a good practice for you as the ability to present and organize is a fundamental, yet undervalued part of Data Science.
If you choose to present on the last session, fill out this form available here
- A short presentation explaining your workflow and thought process (Should not exceed more than 5 minutes)
- A short demo
- 2-3 questions from the instructor
The source code can be submitted on the GitHub repository for a better profile!
- Performing Exploratory Data Analysis (EDA) on a dataset and showcasing your observations
- Training and deploying a Machine Learning model (Does not have to be too advanced)
Feel free to check out popular websites such as Kaggle, Medium, Towards Data Science or be creative and try something of your own by looking for some open-source data
If you have any questions regarding the Bootcamp, feel free to email datasciencebootcamp@nyu.edu