Group Project 2 Description:

Your group members decide to run a startup company and pursue your entrepreneurship on peer-to-peer lending. You identifiedthe business platform, i.e., the lending club(https://www.lendingclub.com/), the largest peer-to-peer online marketplace bringing together borrowers and lenders. You will build a startupinstitutional investment company (see the definition of the investment company in the lending club: https://www.lendingclub.com/investing/institutional/team) using this platform to identify some segment of borrowers. However, you do not have enough funding of your own and plan to attract the venture funding (NOT your mortgage, it is too risky :)) to provide your startup funds.

Several venture funds are interested in your business idea and will arrange a meeting with your group members. Please get your document, presentation, and technical data mining script ready before the meeting, and you will receive GO/NO GO during the business meeting. Here is the list of documents you need to submit for the business meeting/course grading.

Part 1 Python Notebook Submission (50 points):

Improved iPython notebook (your Python code and running results) to process the historical lending data and predict Default or Stand-standing.

Please make a note that you start with a Python Notebook that partially works and requires you to fill in the missing Python statement. The Python Notebook is on Google Drive. The data and Python notebook is available on theGoogle shared drive Links to an external site.(https://drive.google.com/drive/u/0/folders/11sC-Jq7YNUfL3E5c7KxNe9gDz0We6qdXLinks to an external site.). The example Python notebook is already under the subdirectory Note-Books (Note-Books/Project2-Notebook.ipynb). The input data directory is in (input/accepted-200000.csv). The directory contains more (big) data. You do not need to reimplement the Python Notebook. You will add machine learning algorithms (such as Neural Networks, Support Vector Machines, Naive Bayes model), modify the data preprocessing procedures, and tune the parameters. Your technical objective is to improve the performance metric (The Python Notebook uses the Area under Receiver Operator Characteristics (AUROC)). The higher the improvement you make in your customized Python notebook, the high your technical component in this project. For your reference: the test set AUROC score of the baseline method is around 0.72.

Some description of the data: in this project, we have big data, more than 1Million data records. I create two datasets: one is the complete data set, and the other is a partial dataset. I picked the first 20% of the dataset. The data might still be relevantly big; you can sample data!

Hint: Check out the videoLinks to an external site. that goes through the provided script to start.

Part 2 Document Submission (50 points)

• A Three-Page Business Plan for your lending company that participates in the lending club. Please refer to Wikipedia Business PlanLinks to an external site.:https://en.wikipedia.org/wiki/Business_planLinks to an external site.. Please include how to build your company around machine learning-assisted portfolio management. No more than a three-page BUSINESS plan (points will be if you pass the page limit. (25pts)
• Five PowerPoint slides for an Elevator Pitch. (5pts)
• A short video of up to ten minutes presenting your project for an Elevator Pitch. Please either upload the video or provide a link to the video. (20pts)
  • You can either submit your PowerPoint with companion audio.
  • (Preferred) You can use WebEx to record your presentation; each person will record their sound track with video when they present.