In this liveProject, you’ll jump into the role of a data scientist working for an online bookstore. Your boss wants you to build a new recommendation system to help the marketing team match customers with a book that suits their interests. As the backbone of this new system, you’ve decided to create a graph network that will plot and analyze the relationship data of your platform’s users. To do this, you’ll need to import your data into pandas and transform it into an edge list, then build a network from the list. Once that’s accomplished, you’ll visualize and analyze the list to check its accuracy before you present your results as a web application that’s easy for the non-technical marketing team to use.
For this liveProject, you’ll be provided with real customer data from manning.com!
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This project is designed (using multiple help levels) to be accessible to those of a wide skill range, the following pre-requisites will enable smoother usage of the course. Having said this the course should be doable for all skills levels.
- Basics of Python
- Basics of pandas
- Basics of Jupyter notebook
- Ability to read and learn from Python documentation
- Ability to install modules in Python
- Utilizing virtual environments
you will learn
In this liveProject you’ll learn to create a graph network that’s perfect for data with rich relationships. The skills for interpreting complex platforms and connection data are easily transferable to business, eCommerce, and scientific analysis.
- Uploading data into pandas DataFrames and rearranging the data
- pandas data manipulation and analysis
- Building networks with Python
- Visualizing and analyzing graph networks
- Presenting results to potential clients