- Feature Engineering
- Classification Algorithms
- Scikit Learn (Machine Learning Library)
- Random Forest Algorithm
- Applied Machine Learning
- Predictive Modeling
- Python Programming
- Decision Tree Learning
- Model Evaluation
- Regression Analysis
- Unsupervised Learning
- Supervised Learning
Applied Machine Learning in Python
Completed by Francis Dave Perez Cabanting
October 19, 2020
31 hours (approximately)
Francis Dave Perez Cabanting's account is verified. Coursera certifies their successful completion of Applied Machine Learning in Python
What you will learn
Describe how machine learning is different than descriptive statistics
Create and evaluate data clusters
Explain different approaches for creating predictive models
Build features that meet analysis needs
Skills you will gain
