- Classification Algorithms
- Exploratory Data Analysis
- Predictive Modeling
- Decision Tree Learning
- Scikit Learn (Machine Learning Library)
- Random Forest Algorithm
- Applied Machine Learning
- Regression Analysis
- Model Evaluation
- Machine Learning
- Data Preprocessing
Interpretable Machine Learning Applications: Part 2
Completed by Shikha Verma
October 5, 2021
1 hours (approximately)
Shikha Verma's account is verified. Coursera certifies their successful completion of Interpretable Machine Learning Applications: Part 2
What you will learn
Apply Local Interpretable Model-agnostic Explanations (LIME) as a machine learning interpretation
Explain individual predictions being made by a trained machine learning model.
Add aspects for individual predictions in your Machine Learning applications.
Skills you will gain
