Machine Learning / Data Science Lifecycle:
- Define objective
- Data analysis
- Feature engineering
- Model development and evalualtion
- Deployment
Topic: SharpestMinds weekly touchbase
Join Zoom Meeting https://us04web.zoom.us/j/3832725619?pwd=aFFicG5XWWx6TGNYQlF2b0l2RmNRZz09
Meeting ID: 383 272 5619
Passcode: rjSn4i
We will use the conda package manager to setup our development environment. You can download the software on this page.
Once installed, build the environment by running:
cd sm-202011
conda env create
Once all the packages have been installed, activate it by
conda activate sm-202011
The goal of this project is to develop a machine learning model to predict which customers will default on their loan. This project has many of the challenges you might encounter on data science projects in industry: missing records, categorical variables, label you must create yourself. It's a fun problem that is also directly revelant to the banking industry.
- Data source: https://www.kaggle.com/wordsforthewise/lending-club
- Kaggle kernels you might find useful: