Interpretable machine learning applications: Part 3
Completed by Kavin Chandrasekar
April 12, 2026
1 hours (approximately)
Kavin Chandrasekar's account is verified. Coursera certifies their successful completion of Interpretable machine learning applications: Part 3
What you will learn
Import, explore and normalize real world data (HELOC) for evaluating the risk performance of mortgage applications
Train and test a prediction model as a Sequential model based Artificial Neural Network (ANN)
Generate explanations based on profiles of mortgage applicants closest to the individual requesting the explanation.
Skills you will gain
- Category: Deep Learning
- Category: Applied Machine Learning
- Category: Mortgage Loans
- Category: Feature Engineering
- Category: Tensorflow
- Category: Risking
- Category: Artificial Neural Networks
- Category: Keras (Neural Network Library)
- Category: Data-Driven Decision-Making
- Category: Consumer Lending
- Category: Machine Learning Software
- Category: Model Evaluation
