- Data Analysis
- Performance Tuning
- Scikit Learn (Machine Learning Library)
- Supervised Learning
- Regression Analysis
- NumPy
- Classification And Regression Tree (CART)
- Machine Learning
- Exploratory Data Analysis
- Data Science
- Predictive Modeling
- Feature Engineering
Introduction to Machine Learning: Supervised Learning
Completed by Tzu Chjeh Wu
July 7, 2024
40 hours (approximately)
Tzu Chjeh Wu'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
