Build Your Machine Learning Pipeline in These 4 Simple Steps - Loan Prediction Scikit-Learn Example

Develop a comprehensive machine learning pipeline for loan prediction using scikit-learn in this 59-minute tutorial. Learn to implement key components including data ingestion, cleaning, feature engineering, augmentation, model building, improvement, and deployment. Follow along with four Jupyter notebooks covering different aspects of the pipeline, from initial data processing to model reuse for predictions. Gain hands-on experience with pandas, scikit-learn, and other essential tools for data analysis and machine learning in Python.

- Start of the Video
- Intro
- Jupyter Notebook #1 - Data Ingest, cleaning, ML algos
- Jupyter Notebook #2 - Adding Feature Engineering
- Jupyter Notebook #3 - Data Augmentation
- Jupyter Notebook #4 - Using saved model and scoring with test data
- Recap