This repository contains my approach to solving the business problems of the Coursera course Applied Data Science Capstone offered by IBM. ( ⭐️ Star repo on GitHub — it helps! )
Final Certificate of the course can be viewed from this link.
The questions I aim to answer in this project are the following:
- List and visualize all major parts of Mumbai City with top existing infrastructure.
- What are the best locations in Mumbai as per infrastructure?
- Which areas have the potential for the development of infrastructure of different kinds?
- Which all areas lack the infrastructure facilities?
- What is the best place to stay within a city for all vital infrastructure facilities? And few bonus analysis.
An ipython notebook is used for data preprocessing, machine learning analysis and data visualiation. All core scripts are in Week 5 Final .ipynb files" folder. All result output are in result folder and the detailed description of the data can be found in Week 5 section of repository.
I build this capstone undertaking to give you a sample of what data scientists go through in real life when working with data. It uses location data and different location data providers, such as Foursquare. This task exhibits how to make RESTful API calls to the Foursquare API to retrieve information about venues in different neighborhoods around the globe. During the project, I have figured out how to be creative in circumstances where data are not readily available by scratching web information and parsing HTML code. I have used Python and its pandas library to manipulate data, which helped me to refine my skills for exploring and analyzing data. At long last, I have utilized the Folium library to extraordinary maps of geospatial information and to impart my outcomes and discoveries.
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