- Decision Tree Learning
- Model Evaluation
- Data Science
- Logistic Regression
- Data Preprocessing
- Feature Engineering
- NumPy
- Machine Learning
- Scikit Learn (Machine Learning Library)
- Regression Analysis
- Applied Machine Learning
- Random Forest Algorithm
Introduction to Machine Learning: Supervised Learning
Completed by ILZE PELECE
March 26, 2024
40 hours (approximately)
ILZE PELECE's account is verified. Coursera certifies their successful completion of Introduction to Machine Learning: Supervised Learning
What you will learn
Use modern machine learning tools and python libraries.
Compare logistic regression’s strengths and weaknesses.
Explain how to deal with linearly-inseparable data.
Explain what decision tree is & how it splits nodes.
Skills you will gain
